Dorsal spinal column characterization with evoked potentials

ABSTRACT

This disclosure relates to methods, devices, and systems for delivering and adjusting stimulation therapy. In one example, a method comprising delivering, by a stimulation electrode, electrical stimulation as a candidate therapy to a patient according to a set of candidate therapy parameters, the stimulation electrode located in proximity to the dorsal column of a patient; sensing, by a sensing electrode, an electrically evoked compound action potential (eECAP) signal in response to the delivery of the electrical stimulation; and classifying, by a processor, the sensed eECAP signal generated in response to the application of the candidate therapy relative to an eECAP baseline is disclosed.

RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.15/704,893, which was filed on Sep. 14, 2017 and which claims thebenefit of U.S. Provisional Application No. 62/395,727, which was filedSep. 16, 2016. The contents of each of U.S. patent application Ser. No.15/704,893 and U.S. Provisional Application No. 62/395,727 isincorporated herein in its entirety.

TECHNICAL FIELD

The disclosure relates to medical therapy and, more particularly,electrical stimulation.

BACKGROUND

Medical devices, including implantable medical devices (IMDs), may beused to treat a variety of medical conditions. Medical electricalstimulation devices, for example, may deliver electrical stimulationtherapy to a patient via external and/or implanted electrodes.Electrical stimulation therapy may include stimulation of nerve tissue,muscle tissue, the brain, the heart, or other tissue within a patient.In some examples, an electrical stimulation device is fully implantedwithin the patient. For example, an implantable electrical stimulationdevice may include an implantable electrical stimulation generator andone or more implantable leads carrying electrodes. Alternatively, theelectrical stimulation device may comprise a leadless stimulator. Insome cases, implantable electrodes may be coupled to an externalelectrical stimulation generator via one or more percutaneous leads orfully implanted leads with percutaneous lead extensions.

Medical electrical stimulators have been proposed for use to relieve avariety of symptoms or conditions such as chronic pain, tremor,Parkinson's disease, depression, epilepsy, migraines, urinary or fecalincontinence, pelvic pain, sexual dysfunction, obesity, andgastroparesis. An electrical stimulator may be configured to deliverelectrical stimulation therapy via leads that include electrodesimplantable proximate to the spinal cord, pelvic nerves,gastrointestinal organs, sacral nerves, peripheral nerves, or within thebrain of a patient. Stimulation proximate the spinal cord, proximate thesacral nerve, within the brain, and proximate peripheral nerves areoften referred to as spinal cord stimulation (SCS), sacralneuromodulation (SNM), deep brain stimulation (DBS), and peripheralnerve stimulation (PNS), respectively.

SUMMARY

In general, this disclosure relates to adjusting electrical stimulationparameters associated with electrical stimulation delivered to a patientbased on sensing of electrically evoked compound action potential(eECAP) in a patient. Various examples as described herein compriseusing electrically evoked compound action potential (eECAP) as a tool tocharacterize nerve propagation or excitability changes in response to aspecific therapeutic or diagnostic interventions, e.g., stimulationtherapy, for example in the form of applied electrical stimulation, andusing this information to inform and configure, e.g., optimize, futuretherapeutic modalities. The applied stimulation therapy may beconfigured, e.g., optimized, in a manner to suppress or enhance signalpropagation on certain nerve fiber types, or to choose betweenequivalent stimulation therapies where one is more advantageous forother reasons (e.g., less current draw from the battery of the implantedmedical device providing the applied stimulation therapy).

In various examples, the eECAP may be evoked in response to theapplication of electrical stimulation therapy defined according to a setof stimulation parameters. The sensed eECAP signal may be sensed andanalyzed in view of one or more eECAP parameters, either directlymeasured from the sensed eECAP signal, or derived from the sensed eECAPsignal. The eECAP parameters may then be used to determine whether oneor more adjustments to the electrical stimulation parameters of thepreviously applied stimulation therapy can be made to better optimize acharacteristic of the stimulation, and/or to better optimize operatingparameters of the system providing the stimulation therapy. The eECAPsignal can be sensed by a sensor which is located relatively furtherfrom the targeted stimulation nerve site, or a sensor which is placedin, or in close proximity to, the targeted stimulation nerve site. Insome examples, the sensor can be built-in with one or more stimulationelectrodes. In other examples, the same electrode, or electrodes, may beconfigured to deliver stimulation signals and detect the eECAP signal.In other examples, one or more of the electrodes configured to sense theeECAP are different from the electrode or electrodes configured todeliver the stimulation therapy.

In some examples, a method consistent with the disclosure includes amethod comprising: delivering, by a stimulation electrode, electricalstimulation as a candidate therapy to a patient according to a set ofcandidate therapy parameters, the stimulation electrode located inproximity to the dorsal column of a patient; sensing, by a sensingelectrode, an electrically evoked compound action potential (eECAP)signal in response to the delivery of the electrical stimulation;classifying, by a processor, the sensed eECAP signal generated inresponse to the application of the candidate therapy relative to aneECAP baseline; and determining, by the processor, if the sensed eECAPsignal is different over the eECAP baseline based on at least oneparameter used in classifying the sensed eECAP signal.

In some examples, the disclosure describes a system comprising: one ormore electrodes; a stimulation generator configured to apply stimulationtherapy via the one or more electrodes based on a set of stimulationtherapy parameters; and a processor configured to: generate thecandidate therapy parameters, control the stimulation generator toprovide the candidate stimulation therapy to the one or more electrodesbased on the candidate therapy parameters, sense an electrically evokedcompound action potential (eECAP) signal generated in response to theapplication of the candidate stimulation therapy, classify the sensedeECAP signal based on an eECAP baseline; and determine if the sensedeECAP signal is different over the eECAP baseline based on at least oneparameter used in classifying the sensed eECAP signal.

In some examples, the disclosure describes a system comprising: one ormore electrodes; a stimulation generator configured to apply stimulationtherapy via the one or more electrodes based on a set of stimulationtherapy parameters; and a processor configured to: receive a detectedsignal including an evoked compound action potential (eECAP) in responseto the application of the stimulation therapy; analyze the detectedsignal; and adjust at least one of the stimulation parameters based onthe analysis of the detected signal.

In some examples, the disclosure describes a system comprising: meansfor applying stimulation therapy to a patient according to a set ofstimulation therapy parameters; means for sensing a signal including anelectrically evoked compound action potential (eECAP) in response to theapplication of the stimulation therapy; and means for classifying thesensed eECAP signal at least in part based on a baseline eECAP.

In some examples, the disclosure describes a non-transitory computerreadable medium comprising instructions for causing a programmableprocessor to perform any of the methods described herein.

In some examples, a method consistent with the disclosure includes amethod comprising: delivering, by a stimulation electrode, electricalstimulation as a baseline therapy to a patient according to a set ofbaseline therapy parameters, the stimulation electrode located inproximity to the dorsal column of the patient; sensing, by a sensingelectrode, an electrically evoked compound action potential (eECAP)signal in response to the delivery of the electrical stimulation as aneECAP baseline; determining, by a processor, a change to a therapyparameter to generate a candidate therapy having a set of candidatetherapy parameters; delivering, by the stimulation electrode, electricalstimulation based on the candidate therapy to the patient according tothe candidate therapy parameters; sensing, by the sensing electrode, anelectrically evoked compound action potential (eECAP) signal in responseto the delivery of the electrical stimulation based on the candidatetherapy; classifying, by the processor, the sensed eECAP signalgenerated in response to the application of the candidate therapyrelative to an eECAP baseline; determining, by the processor, if thesensed eECAP signal is different over the eECAP baseline based on atleast one parameter used in classifying the sensed eECAP signal; andestablishing, by the processor, a parameter boundary for the at leastone parameter as equivalent to the baseline if the sensed eECAP signalis determined to be different over the eECAP baseline.

In some examples, a method consistent with the disclosure includes amethod comprising: delivering, by a stimulation electrode, electricalstimulation as a baseline therapy to a patient according to a set ofbaseline therapy parameters, the stimulation electrode located inproximity to the dorsal column of the patient; sensing, by a sensingelectrode, an electrically evoked compound action potential (eECAP)signal in response to the delivery of the electrical stimulation as aneECAP baseline; generating, by a processor, a candidate therapy having aset of candidate therapy parameters; delivering, by the stimulationelectrode, electrical stimulation as a candidate therapy to the patientaccord to the set of candidate therapy parameters; sensing, by thesensing electrode, an electrically evoked compound action potential(eECAP) signal in response to the delivery of the electrical stimulationbased on the candidate therapy; classifying, by the processor, thesensed eECAP signal generated in response to the application of thecandidate therapy relative to an eECAP baseline; and determining, by theprocessor, if the sensed eECAP signal is different over the eECAPbaseline based on at least one parameter used in classifying the sensedeECAP signal, wherein determining if the sensed eECAP signal isdifferent over the eECAP baseline comprises deterring that the candidatetherapy is equivalent to the baseline therapy if the sensed eECAP signalis not different over the eECAP baseline, or that the candidate therapyis not equivalent to the baseline therapy if the sensed eECAP signal isdifferent over the eECAP baseline.

In some examples, a method consistent with the disclosure includes amethod comprising: defining, by a processor, one or more targetparameters for an electrically evoked compound action potential (eECAP)signal as a target eECAP; defining, by the processor, one or morecandidate therapy parameters; generating, by the processor, a candidatetherapy based on as set of the defined candidate therapy parameters;delivering, by a stimulation electrode, electrical stimulation based onthe generated candidate therapy to a patient according to the set ofcandidate therapy parameters, the stimulation electrode located inproximity to the dorsal column of the patient; sensing, by a sensingelectrode, an electrically evoked compound action potential (eECAP)signal in response to the delivery of the candidate therapy;classifying, by the processor, the sensed eECAP signal generated inresponse to the application of the candidate therapy relative to thetarget eECAP; and determining, by the processor, if the sensed eECAPsignal matches the target eECAP based on at least one parameter used inclassifying the sensed eECAP signal, wherein determining if the sensedeECAP signal matches the target eECAP comprises deterring that the atleast one parameter used in classifying the sensed eECAP signal matchesthe corresponding parameter or parameters of the target eECAP.

In some examples, a method consistent with the disclosure includes amethod comprising: delivering, by a stimulation electrode, electricalstimulation as a baseline therapy to a patient according to a set ofbaseline therapy parameters, the stimulation electrode located inproximity to the dorsal column of the patient; ceasing delivery of theelectrical stimulation by the stimulation electrode; sensing, by asensing electrode, an electrically evoked compound action potential(eECAP) signal in response to the delivery of the electrical stimulationas an eECAP signal; classifying, by a processor, the sensed eECAP signalgenerated in response to the application of the baseline therapyrelative to an eECAP baseline; and determining, by the processor, if thesensed eECAP is a particular eECAP, the determination of whether thesensed eECAP is a particular eECAP based on one or more parameters usedto classify the sensed eECAP signal; and determining, by the processor,if more therapy is to be delivered to the patient based on thedetermination of whether the sensed eECAP was or was not the particulareECAP.

In some examples, a method consistent with the disclosure includes amethod comprising: delivering, by a stimulation electrode, electricalstimulation as a baseline therapy to a patient according to a set ofbaseline therapy parameters, the stimulation electrode located inproximity to the dorsal column of the patient; ceasing delivery of theelectrical stimulation by the stimulation electrode; sensing, by asensing electrode, an electrically evoked compound action potential(eECAP) signal in response to the delivery of the electrical stimulationas an eECAP signal; classifying, by a processor, the sensed eECAP signalgenerated in response to the application of the baseline therapy;determining, by the processor, if the sensed eECAP is a particulareECAP, the determination of whether the sensed eECAP is a particulareECAP based on one or more parameters used to classify the sensed eECAPsignal; determining, by the processor, if a time period has expiredfollowing ceasing delivery of the electrical stimulation; anddetermining, by the processor, if more therapy is to be delivered to thepatient based on the determination of whether the sensed eECAP was orwas not the particular eECAP and whether the time period has expired.

The details of one or more examples are set forth in the accompanyingdrawings and the description below. Other features, objects, andadvantages will be apparent from the description and drawings, and fromthe claims.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a schematic diagram illustrating an example implantablestimulation system including a pair of implantable stimulation electrodearrays carried by implantable leads.

FIG. 2 is a conceptual diagram illustrating an example system that isconfigured to deliver sacral neuromodulation to a patient.

FIG. 3 is a functional block diagram illustrating example components ofan IMD, such as the IMD shown in FIG. 1.

FIG. 4 is a functional block diagram illustrating example components ofan external programmer for an IMD, such as the external programmer andIMD shown in FIG. 1.

FIG. 5 is a block diagram illustrating an example system that includesan external device, such as a server, and one or more computing devices,that are coupled to IMD and external programmer shown in FIG. 1 via anetwork.

FIG. 6 illustrates a pair of graphs, each graph illustrating astimulation pulse, and the sensed eECAP signal generated in response tothe stimulation pulse, respectively.

FIG. 7 illustrates a graph of peak amplitudes of eECAP from nerve fibersafter cessation of an applied burst of electrical stimulation inaccordance with various techniques consistent with this disclosure.

FIG. 8 illustrates a graph showing various measurements taken directlyfrom and derived from eECAP from nerve fibers after cessation of anapplied burst of electrical stimulation in accordance with varioustechniques consistent with this disclosure.

FIG. 9 is a flow diagram illustrating an example method for adjustingelectrical stimulation therapy parameters based on a sensed eECAP inresponse to applied stimulation in accordance with various techniquesconsistent with this disclosure.

FIG. 10 is a flow diagram illustrating an example method for testingelectrical stimulation therapy parameters based on a sensed eECAP inresponse to applied stimulation in accordance with various techniquesconsistent with this disclosure.

FIG. 11 is a flow diagram illustrating an example method for adjustingelectrical stimulation therapy parameters based on a sensed eECAP inresponse to applied stimulation in accordance with various techniquesconsistent with this disclosure.

FIG. 12 is a flow diagram illustrating an example method for adjustingelectrical stimulation therapy parameters based on a sensed eECAP inresponse to applied stimulation in accordance with various techniquesconsistent with this disclosure.

FIG. 13 a flow diagram illustrating an example method for adjustingelectrical stimulation therapy parameters based on a sensed eECAP inresponse to applied stimulation in accordance with various techniquesconsistent with this disclosure.

DETAILED DESCRIPTION

This disclosure includes systems, devices, and methods relating toadjusting electrical stimulation parameters that define electricalstimulation delivered to a patient. A patient as used herein in generalrefers to a human patient, but is not limited to humans, and may includeanimals. Various references to a “test patient” as used herein mayinclude animals used to receive test stimulation patterns and to collectdata related to the stimulation tests according to the varioustechniques described herein. In therapeutic or intervention typeapplications, a patient may receive electrical stimulation therapy torelieve a variety of symptoms or conditions. In some cases, a physicianor clinician may manually adjust electrical stimulation parametersaccording to patient feedback, such as the patient's perception onreduction in pain levels or any changes in symptoms. However, patientfeedback can be inconsistent over time and it is also subjective. Inthis manner, it may be difficult to determine the most appropriatestimulation parameters to relive the patient's symptoms or conditionsand provide improved system performance (e.g., efficient energy usageand targeted therapy delivery).

As discussed herein, systems, devices, and methods are described foradjusting electrical stimulation parameters based on a detectedelectrically evoked compound action potential (eECAP). The eECAP may beevoked in response to the application of electrical stimulation therapythat is defined according to a set of stimulation parameters.Adjustments to the electrical stimulation parameters based on thedetected eECAP may provide more objective information than patientfeedback. In addition, eECAP detection may allow a system to provideclosed-loop stimulation control. Incorporation of eECAP into adjustment,and/or titration, of stimulation parameters may allow for stimulationsystems to provide stimulation therapy that uses less energy, moretargeted stimulation delivery to desired tissues, and/or improvedtherapeutic efficacy as compared to techniques that do not incorporateeECAP detection. In some examples, dorsal column stimulation therapy orother electrical stimulation therapy is provided according to a therapyprogram with stimulation parameters, such as current or voltageamplitude, frequency, and/or pulse width, that are selected to provide alevel of therapy, such as a reduction in the level of or elimination ofpain felt by the patient. Spinal cord stimulation may also includestimulation of dorsal nerve roots. Further, stimulation is not limitedto stimulation of the spinal cord, and may be applied to peripheralnerves or their end organs. Further, peripheral stimulators do not haveto be implanted devices, and they may also comprise non-electricalstimuli (e.g., mechanical, thermal).

Spinal cord stimulation (SCS) in patients has historically consisted offixed lower frequency, (e.g., approximately 50 Hz), periodic delivery ofelectrical impulses to the dorsal column of the patient for the purposeof inducing paresthesia. The paresthesia serves to mask pain felt inspecific regions of the body, such as the lower back or legs. Sensorysignals, in this case, the periodic electrical impulses from the spinalcord stimulator or the pain signal itself, are relayed to the brain viathe dorsal columns of the spinal cord. The dorsal column consists ofmultiple sensory nerve fiber types, categorized generally by the fiberthickness and their associated signal propagation velocities. Very thick(13-20 μm) Aα fibers have action potential propagation velocities around100 m/s and are associated with proprioception. Thick diameter (6-12 μm)Aβ fibers are heavily myelinated with action potential propagationvelocities approaching 60 m/s. Paresthesia with SCS is thought to resultfrom modulation of Aβ fibers. Thinner diameter (2-5 μm), myelinated Aδfibers have action potential propagation velocities on the order of 10m/s. Unmyelinated C fibers (0.2 μm-1.5 μm) transmit signals at 2 m/s.Both Aδ and C fibers are responsible for transmitting pain signals tothe brain, with Aδ and C fibers contributing acute and burning paincharacteristics, respectively. The dorsal column is part of an ascendingpathway, comprising nerve such as Aα Type I or Aα Type II nerve fibers,that is important for fine touch and conscious proprioception.

There are a number of factors which may affect the propagation ofsignals along the spinal cord. Examples include the presence or absenceof certain chemical factors, disease state, or electrical stimulation.In some instances, it is desirable to adapt a therapeutic interventionwith a patient based on the measured signal propagation characteristicsof the spinal cord. One method for quantifying these characteristics iswith the electrically evoked compound action potential (eECAP). Invarious examples, an electrical stimulus is applied to the spinal cordof a patient at a particular location, and the resultant eECAP isrecorded. The sensing and measurement of these eECAP signals are notlimited to the spinal cord, and may also be recorded in other locationsbesides the spinal cord, such as peripheral nerves, or for example fromwithin the brain.

In view of these factors, other parameters for delivery of SCS therapiesthat are different from the historically applied SCS therapies mayprovide efficacy in treatment for a particular patient. For example, SCSsystems which deliver stimulation at a higher frequency, for example ata 10 kHz frequency are known, which utilize a much faster frequency thantraditional SCS therapies provided at the 50 Hz frequency. The assertedadvantage of the application of the higher frequency therapy is thatpatients have reported masking of the pain sensation(s) without theassociated paresthesia sensation sometimes experienced when using thelower frequency SCS therapies. However, at least one drawback to thesehigher frequency systems is the need for extremely frequent batteryrecharge owing to the two-hundred times faster stimulation frequency.Further, these higher frequency systems can lose efficacy and requiremore frequent in-clinic therapy updates over traditional systems thatdeliver the lower frequency SCS therapies. For patients where 10 kHzneurostimulation results in adequate short term therapy but isunacceptable from a battery draw-down and durability perspective,characteristics of the eECAP, as described herein, may be used to selectan alternative stimulation paradigm which results in significantly lessbattery-referred current consumption and is more robust againstanticipated efficacy loss, while maintaining a same or at least anadequate level of efficacy for the patient's symptoms.

As noted above, the systems, devices, and methods described hereinrelate to using the eECAP as a tool to characterize nerve propagationchanges in response to specific therapeutic or diagnostic interventions(stimulation therapy), and using this information to inform and optimizefuture therapeutic modalities. The therapy provided may be optimized ina manner to suppress or enhance signal propagation on certain fibertypes in a patient, or to choose between equivalent therapies where oneis more advantageous for other reasons (e.g., less current draw from thebattery of the implanted medical device delivering the therapy). TheeECAP may be evoked in response to the application of electricalstimulation therapy that is defined according to a set of stimulationparameters. Adjustments to the electrical stimulation parameters basedon the detected eECAP may provide more objective information thanpatient feedback. In addition, eECAP detection may allow a system toprovide closed-loop stimulation control. Incorporation of eECAP intoadjustment, and/or titration, of stimulation parameters may allow forstimulation systems to provide stimulation therapy that uses lessenergy, more targeted stimulation delivery to desired tissues, and/orimproved therapeutic efficacy as compared to techniques that do notincorporate eECAP detection. The eECAP may be detected by an electricalsensing system such as one within an implantable medical device, or inelectrical communication with said device. The sensing system mayinclude one or more electrodes positioned at some distance away from thesite of the application of the electrical stimulation.

In some examples, detection, or the lack thereof, of the presence of theeECAP in response to stimulation provided at a particular set of therapyparameters is used to program initial stimulation therapy parametersprovided to a patient via an implantable medical device. In otherexamples, the detection of eECAP in response to stimulation provided ata particular set of therapy parameters may be used to adjust existingstimulation therapy parameters. The programming or adjustment ofstimulation therapy parameters may be manual or automatic. The presenceor absence of an eECAP in response to a set of stimulation therapyprogram may be used as a biomarker in programming and adjustment topatient stimulation.

For example, during initial programming, an IMD may start providingstimulation according to an initial therapy parameter set, e.g.,including a relatively higher frequency, such as 15 kHz. An eECAP signalthat is generated by one or more nerve fibers as a result of the appliedstimulation is sensed, and may then be stored as a baseline signal.Following establishment of the baseline, one or more parameters of thestimulation therapy may be adjusted. For example, the frequency of theapplied stimulation is lowered in order to generate a new set of therapyparameters for a candidate therapy. The candidate therapy is thenapplied to the patient, and the resulting eECAP generated as a result ofthe application of the candidate therapy is sensed and categorized withrespect to the stored baseline signal.

Categorization of the baseline eECAP signal and the eECAP signalgenerated in response to the applied candidate therapy or candidatetherapies is not limited to any particular type of categorization, andrefers to any type of analysis of the eECAP signals. Categorization mayinclude quantification of any type of parameter the can be eitherdirectly measured from an eECAP signal, or derived from a measurableparameter of an eECAP signal. An example of a parameter associated withan eECAP signal would include determination of an amplitude of the eECAPsignal at some predetermine time following cessation of the applicationof the electrical stimulation therapy. Examples of parameters associatedwith an eECAP signal are not limited to any particular parameter or typeof parameter. Further non-limiting examples of parameters associatedwith eECAP signals are provided throughout this disclosure.

In various examples, one or more of the parameters of the eECAP signalare determined, the eECAP parameters derived from an initial stimulationtherapy having known therapy parameters as provided to a patient,wherein the eECAP parameters and eECAP are stored as part of a baseline.A candidate therapy having one or more therapy parameters that aredifferent from the therapy parameters of the initial stimulation therapyare generated, and applied to the patient. The eECAP signal generated inresponse to each of the applied candidate therapies is sensed, and oneor more parameters related to the sensed eECAP generated in response tothe applied candidate therapy are determined, and compared to theparameters stored with respect to the baseline. By comparing theparameters of the eECAP generated in response to the applied candidatetherapy to the baseline parameters, a determination may be made as towhether the eECAP generated in response to the applied candidate therapyis different from the eECAP generated by the initial stimulationtherapy.

The determination of “different from” is not limited to any particularcriteria, and for example may be based on whether a particular parameterdetermined for the eECAP generated in response to the applied candidatetherapy falls within a predefined range of values with respect to thevalue for that same parameter determined for the eECAP signal generatedin response to the application of the initial stimulation therapy, e.g.,the baseline value for that parameter. The criteria used for making thedetermination as to whether the eECAP signal generated in response tothe application of the candidate therapy is different from the eECAPsignal generated in response to the application of the initialstimulation therapy are not limited to any particular criterial, as manyparameters associated with eECAP signals are possible, and arecontemplated by at least the examples, and the equivalents thereof, asfurther provided in this disclosure. Using these techniques, a candidatetherapy that provides the same (i.e., not different from) eECAP responseas the initial therapy, based on one or more compared parameters, butusing a different set of therapy parameters may be determined using themeasured eECAP as the basis for performing the comparisons. By using adifferent set of therapy parameters, the candidate therapy may thereforeprovide an equal or a substantially equal level of treatment efficacy tothe patient while providing other performance advantages, such as longerbattery life between recharges or battery replacements, compared to theinitial stimulation therapy.

In other examples, the baseline parameters are associated with a targeteECAP response that is not necessarily a result of a sensed eECAPresulting from applied stimulation therapy, but instead a proposedresponse. In various examples, one or more candidate therapies having aset of therapy parameters are proposed, and the candidate therapies aregenerated and applied to the patient. The sensed eECAP signal generatedin response to each of the applied candidate therapies can then besensed and analyzed to determine if the candidate therapy resulted in aneECAP signal the meets one or more criteria established for the targeteECAP. The criteria for determining if the candidate therapy resulted ingeneration of the target eECAP is not limited to any particularcriteria, and in some examples may be based on a determination that oneor more of the parameters associated with the eECAP generated byapplication of the candidate therapy falls within a predetermined rangeof the value of the corresponding parameter of the target eECAPresponse, or exceeds a threshold value set by the correspondingparameter of the target eECAP response.

In various examples, the adjustment to the therapy parameters used togenerate the candidate therapies may include an increase or may includea decrease in any of the therapy parameters of the applied stimulation,for example, by adjustment to the amplitude, frequency and/or pulsewidth of stimulation pulses. In some examples, the stimulation intensitymay be increased or decreased at predetermined increments, and eachincremental adjustment of the parameters may be used to generate a newcandidate therapy that can then be applied, at separate times to thepatient in order to generate an eECAP that may be sensed and analyzedwith respect to the efficacy and other properties of the associatedcandidate therapy.

In some examples, a given stimulation therapy may be applied to apatient, and the resulting eECAP signal sensed and analyzed to determinewhether the patient's response to that same particular set ofstimulation parameters has changed. In some examples, detection of theeECAP signal in response to a current stimulation therapy program isperformed on an ongoing basis. For example, eECAP signal may be detectedevery few seconds, once a minute, once every few minutes, hourly, dailyor weekly. In some examples, an eECAP signal may be detected in responseto a change in another sensed physiological parameter. For example, theeECAP may detected when there has been a change in activity level orposture of the patient. These changes in activity level and/or postureof a patient may be sensed and/or determined by a same device providingthe stimulation therapy to the patient, or by devices that are not thesame devices providing the stimulation therapy to the patient.

FIG. 1 is a schematic diagram illustrating an example implantablestimulation system 10 including a pair of implantable electrode arraysin the form of stimulation leads 16A and 16B. Although the techniquesdescribed in this disclosure may be generally applicable to a variety ofmedical devices including external and implantable medical devices(IMDs), application of such techniques to IMDs and, more particularly,implantable electrical stimulators such as neurostimulators will bedescribed for purposes of illustration. More particularly, thedisclosure will refer to an implantable spinal cord stimulation (SCS)system for purposes of illustration, but without limitation as to othertypes of medical devices.

As shown in FIG. 1, system 10 includes an IMD 14 and external programmer20 shown in conjunction with a patient 12. In the example of FIG. 1, IMD14 is an implantable electrical stimulator configured for spinal cordstimulation (SCS), e.g., for relief of chronic pain or other symptoms.Again, although FIG. 1 shows an implantable medical device, otherembodiments may include an external stimulator, e.g., withpercutaneously implanted leads, or implanted leads with percutaneouslead extensions. Stimulation energy is delivered from IMD 14 to spinalcord 18 of patient 12 via one or more electrodes disposed on implantableleads 16A and 16B (collectively “leads 16”). In some applications, suchas spinal cord stimulation (SCS) to treat chronic pain, the adjacentimplantable leads 16 may have longitudinal axes that are substantiallyparallel to one another.

Although FIG. 1 is directed to SCS therapy, system 10 may alternativelybe directed to any other condition that may benefit from stimulationtherapy. For example, system 10 may be used to treat tremor, Parkinson'sdisease, epilepsy, urinary or fecal incontinence, sexual dysfunction,obesity, or gastroparesis. In this manner, system 10 may be configuredto provide therapy taking the form of deep brain stimulation (DBS),pelvic floor stimulation, gastric stimulation, or any other stimulationtherapy. In addition, patient 12 is ordinarily a human patient.

Each of leads 16 may include electrodes and the parameters for a programthat controls delivery of stimulation therapy by IMD 14 may includeinformation identifying which electrodes have been selected for deliveryof stimulation according to a stimulation program, the polarities of theselected electrodes, i.e., the electrode configuration for the program,and voltage or current amplitude, pulse rate, and pulse width ofstimulation delivered by the electrodes. Delivery of stimulation pulseswill be described for purposes of illustration. However, stimulation maybe delivered in other forms such as continuous waveforms. Programs thatcontrol delivery of other therapies by IMD 14 may include otherparameters, e.g., such as dosage amount, rate, or the like for drugdelivery.

In the example of FIG. 1, leads 16 carry one or more electrodes that areplaced adjacent to the target tissue of the spinal cord. One or moreelectrodes may be disposed at a distal tip of a lead 16 and/or at otherpositions at intermediate points along the lead. Leads 16 may beimplanted and coupled to IMD 14. Alternatively, as mentioned above,leads 16 may be implanted and coupled to an external stimulator, e.g.,through a percutaneous port. In some cases, an external stimulator maybe a trial or screening stimulation that used on a temporary basis toevaluate potential efficacy to aid in consideration of chronicimplantation for a patient. In additional embodiments, IMD 14 may be aleadless stimulator with one or more arrays of electrodes arranged on ahousing of the stimulator rather than leads that extend from thehousing.

The stimulation may be delivered via selected combinations of electrodescarried by one or both of leads 16, e.g., in bipolar, unipolar, ormultipolar combinations. The target tissue may be any tissue affected byelectrical stimulation energy, such as electrical stimulation pulses orwaveforms. Such tissue includes nerves, smooth muscle, and skeletalmuscle. In the example illustrated by FIG. 1, the target tissue isspinal cord 18. Stimulation of spinal cord 18 may, for example, preventpain signals from traveling through the spinal cord and to the brain ofthe patient. Patient 12 may perceive the interruption of pain signals asa reduction in pain and, therefore, efficacious therapy results.

The deployment of electrodes via leads 16 is described for purposes ofillustration, but arrays of electrodes may be deployed in differentways. For example, a housing associated with a leadless stimulator maycarry arrays of electrodes, e.g., rows and/or columns (or otherpatterns), to which shifting operations may be applied. Such electrodesmay be arranged as surface electrodes, ring electrodes, or protrusions.As a further alternative, electrode arrays may be formed by rows and/orcolumns of electrodes on one or more paddle leads. In some embodiments,electrode arrays may include electrode segments, which may be arrangedat respective positions around a periphery of a lead, e.g., arranged inthe form of one or more segmented rings around a circumference of acylindrical lead. Other electrode and lead configurations may be adaptedfor use with the present disclosure so long as they enable IMD 14 toelectrically stimulate and sense from a target tissue.

In the example of FIG. 1, stimulation energy is delivered by IMD 14 tothe spinal cord 18 to reduce the amount of pain perceived by patient 12.As described above, IMD 14 may be used with a variety of different paintherapies, such as peripheral nerve stimulation (PNS), peripheral nervefield stimulation (PNFS), DBS, cortical stimulation (CS), sacralneuromodulation (SNM), pelvic floor stimulation, gastric stimulation,and the like. The electrical stimulation delivered by IMD 14 may takethe form of electrical stimulation pulses or continuous stimulationwaveforms, and may be characterized by controlled voltage levels orcontrolled current levels, as well as pulse width and pulse rate in thecase of stimulation pulses.

In some examples, IMD 14 may deliver stimulation therapy according toone or more programs. A program defines one or more parameters thatdefine an aspect of the therapy delivered by IMD 14 according to thatprogram. For example, a program that controls delivery of stimulation byIMD 14 in the form of pulses may define a voltage or current pulseamplitude, a pulse width, and a pulse rate, for stimulation pulsesdelivered by IMD 14 according to that program. The program may alsodefine an electrode combination for delivery of the stimulation pulse,including electrode polarities. Moreover, therapy may be deliveredaccording to multiple programs, wherein multiple programs are containedwithin each of a multiple of groups.

During use of IMD 14 to treat patient 12, movement of patient 12 amongdifferent posture states may affect the ability of IMD 14 to deliverconsistent efficacious therapy. For example, leads 16 may migrate towardIMD 14 when patient 12 bends over, resulting in displacement ofelectrodes and possible disruption in delivery of effective therapy.Stimulation energy transferred to target tissue may be reduced due toelectrode migration, causing reduced efficacy in terms of relief ofsymptoms such as pain. As another example, leads 16 may be compressedtowards spinal cord 18 when patient 12 lies down. Such compression maycause an increase in the amount of stimulation energy transferred totarget tissue. In this case, the amplitude of stimulation therapy may bedecreased to avoid causing patient 12 additional pain or unusualsensations, which may be considered undesirable side effects thatundermine overall efficacy.

Also, posture state changes may present changes in symptoms or symptomlevels, e.g., pain level. Reduced efficacy due to increased coupling ordecreased coupling of stimulation energy to target tissue may occur dueto changes in posture and/or activity level associated with patientposture state. To avoid or reduce possible disruptions in effectivetherapy due to posture state changes, IMD 14 may include a posture statemodule that detects the posture state of patient 12 and causes the IMD14 to automatically detect an eECAP response to stimulation in responseto a change in posture state. Based on the detected eECAP, IMD 14determines whether an adjustment to the stimulation parameters isrecommended or otherwise appropriate. For example, a posture statemodule may include a posture state sensor, such as an accelerometer,that detects when patient 12 lies down, stands up, or otherwise changesposture.

A posture state module may include, for example, one or moreaccelerometers that detect when patient 12 occupies a posture state inwhich it may be appropriate to decrease the stimulation amplitude, e.g.,when patient 12 lies down. In some examples, the IMD may automaticallyreduce stimulation amplitude so that patient 12 does not manually haveto do so. The IMD may then detect an eECAP biomarker in response to theadjusted stimulation parameters to determine if the adjustment waseffective. In other examples, the IMD may detect an eECAP biomarker inresponse to stimulation when a change in posture is detected prior tomaking an adjustment to the stimulation parameters. IMD 14 may analyzethe detected eECAP biomarker to determine the appropriate adjustment tothe stimulation parameters. Example posture states may include“Upright,” “Upright and Active,” “Lying Down,” and so forth.

As will be described in greater detail below, in some examples, IMD 14may be configured to automatically adjust stimulation amplitude when itdetects that patient 12 has changed position. In some examples, inresponse to detection of a change in position, IMD 14 determines anappropriate adjustment to the stimulation parameters. In some examples,the determination may include detecting eECAP based on the currentstimulation parameters, and making adjustments to one or morestimulation parameters based on the eECAP biomarker detected. In otherexamples, IMD 14 may select a new set of stimulation parameters storedin a memory based on previously detected eECAP for the same position.

In some examples, stimulation parameter may be configured to be changedat a rate suitable to prevent undesirable effects, e.g., such as theeffects due to the compression of leads 16 towards spinal cord 18 whenpatient 12 lies down. In some examples, IMD 14 may be configured todecrease the stimulation amplitude to a first predetermined loweramplitude value substantially immediately upon detection by IMD 14 thatpatient 12 is lying down. IMD 14 may then evaluate the appropriatenessof the new stimulation amplitude based on eECAP, and make furtheradjustments as necessary. In other examples, IMD 14 may be configured todetect an eECAP biomarker to stimulation upon detection of patient 12lying down. Based on the detected eECAP biomarker, IMD 14 may adjust oneor more stimulation parameters until a desired eECAP biomarker isachieved.

In response to a posture state indication by the posture state module,IMD 14 may change a program group, program, stimulation amplitude, pulsewidth, pulse rate, and/or one or more other parameters, groups orprograms to maintain therapeutic efficacy. When a patient lies down, forexample, IMD 14 may automatically reduce stimulation amplitude so thatpatient 12 does not need to reduce stimulation amplitude manually. Theamount of automatic reduction may be determined, at least in part, basedon a detected eECAP biomarker in the new posture state. In some cases,IMD 14 may communicate with external programmer 20 to present a proposedchange in stimulation in response to a posture state change, for examplefor a first posture state to a second posture state, and receiveapproval or rejection of the change from a user, such as patient 12 or aclinician, before automatically applying the therapy change. In someexamples, posture state detection may also be used to providenotifications, such as providing notification via a wireless link to acare giver that a patient has potentially experienced a fall.

In some examples, IMD 14 may periodically detect eECAP generated inresponse to current stimulation parameters and adjust the currentstimulation parameters if there has been a significant change, i.e.,greater than a predetermined threshold change, to the detected eECAPbiomarker relative to a desired or reference eECAP biomarker. IMD 14 maydetect and analyze eECAP on an hourly, daily, weekly, or monthly basisfor example. In some examples, IMD 14 may initiate an eECAP biomarkerdetection and analysis cycle if a predetermined amount of time haspassed since the last eECAP biomarker detection. The time may reset anytime an eECAP biomarker is detected.

Referring still to FIG. 1, a user, such as a clinician or patient 12,may interact with a user interface of external programmer 20 to programIMD 14. The user interface may include an output device for presentationof information, and an input device to receive user input. Programmingof IMD 14 may refer generally to the generation and transfer ofcommands, programs, or other information to control the operation of IMD14. For example, external programmer 20 may transmit programs, parameteradjustments, program selections, group selections, or other informationto control the operation of IMD 14, e.g., by wireless telemetry. As oneexample, external programmer 20 may transmit parameter adjustments tosupport therapy changes due to posture changes by patient 12. As anotherexample, a user may select programs or program groups. Again, a programmay be characterized by an electrode combination, electrode polarities,voltage or current amplitude, pulse width, pulse rate, and/or duration.A program group may be characterized by multiple programs that aredelivered simultaneously or on an interleaved or rotating basis.

During the delivery of stimulation therapy, patient 12 may make patienttherapy adjustments, i.e., patient adjustments to one or more parametersof a therapy via an input device of a user interface of a programmer, tocustomize the therapy either after patient 12 moves to a differentposture state or in anticipation of the next posture state. In someexamples, IMD 14 may detect an eECAP in response to the therapyadjustment. In some examples, the detected eECAP in response to theadjusted therapy may be stored as indicating effective therapy for aparticular patient state. If the same patient state is detected again,IMD 14 may automatically adjust one or more stimulation parameters inorder to achieve an eECAP biomarker which corresponds to the storedeECAP biomarker. In examples where IMD 14 is in a record mode to storeall patient therapy adjustments associated with a specific patientstate, IMD 14 may implement a method to ensure that patient therapyadjustments are associated with the correct patient state intended bypatient 12 when the therapy adjustment was made. The patient 12 mayoccupy the patient state multiple times such that there are multipleinstances of the sensed patient state. A patient state may be a postureor activity level, for example. In some examples, each time the patient12 occupies a posture state, the patient may enter one or more therapyadjustments.

In some cases, external programmer 20 may be characterized as aphysician or clinician programmer if it is primarily intended for use bya physician or clinician. In other cases, external programmer 20 may becharacterized as a patient programmer if it is primarily intended foruse by a patient, e.g., for entry of patient input to specify patientadjustments to one or more therapy parameters. A patient programmer isgenerally accessible to patient 12 and, in many cases, may be a portabledevice that may accompany the patient throughout the patient's dailyroutine. In general, a physician or clinician programmer may supportselection and generation of programs by a clinician for use bystimulator 14, whereas a patient programmer may support adjustment andselection of such programs by a patient during ordinary use, eithermanually or via other user input media.

External programmer 20 may present eECAP biomarker data stored in IMD 14from the detected eECAP biomarkers to various patient states of patient12. The eECAP data may be acquired by external programmer 20 from IMD 14to generate patient state information, e.g., changes in eECAP biomarkerand associated therapy adjustment. IMD 14 may also store anyassociations between changes in eECAP response, therapy adjustments, andthe patient states for which the therapy adjustments were intendedduring a record mode, i.e., therapy adjustment information. By recordingall therapy adjustments made for a program in each of the patientstates, including each of the multiple instances of the sensed patientstates, external programmer 20 may be able to present therapy adjustmentinformation to the user that indicates a desired eECAP biomarker andcorresponding stimulation parameters based upon parameter use. Forexample, the user may be able to identify the most recent stimulationparameters desired by patient 12, the minimum and maximum allowableamplitudes, or even the quantified number of therapy adjustments toindicate that patient 12 is either satisfied with a program or cannotreadily find suitable parameters for a program with many therapyadjustments.

The therapy adjustment information stored during the record mode may bepresented in any number of different manners. For example, an outputdevice of the user interface may present each program of a group and therespective number of therapy adjustments and the range of suchamplitudes defined by the therapy adjustments. Alternatively, an outputdevice of the user interface may also, or instead, present the last(i.e., most recent) amplitude used by patient 12 to deliver therapy witheach program. In any manner, the therapy adjustment information may bepresented in a graphical, numerical, or textual mode on externalprogrammer 20. The user may be able to customize the presentation of thetherapy adjustment information in other examples.

In some examples, external programmer 20 may utilize the associations ofthe eECAP signal and the therapy adjustments, to posture states in orderto further minimize time needed to program all therapy programs. Whenpresenting the amplitude ranges of the therapy adjustments for eachtherapy program, the user may be able to provide a single confirmationinput that sets the amplitude for all programs to some nominal therapyparameter, for example. The nominal therapy parameter may be a minimumamplitude associated with the program and posture state, the lastamplitude associated with the program and posture state, or some othertherapy parameter already stored by IMD 14 in association with eachtherapy program and posture state. The therapy parameter may be referredto as nominal in the sense that it refers to a parameter value by a namethat is descriptive of the value, rather than to a specific, absoluteparameter value. In cases where a program has not been associated withany therapy adjustment, no new stimulation parameter may be programmedto the program.

In other examples, external programmer 20 may, using a guided algorithm,generate a suggested therapy parameter based upon an eECAP biomarkerresulting from delivery of the therapy according to current stimulationtherapy parameters. In some examples, the current stimulation therapyparameters may be a base stimulation therapy program. The suggestedtherapy parameter may be a specific therapy parameter value that isvisible to the user, but is signified as being suggested by the guidedalgorithm. The guided algorithm may be an equation, set of equations,look-up table, or other technique for generating a suggested therapyparameter that may define stimulation therapy that may be effective whendelivered to patient 12. In this manner, external programmer 20 analyzesthe eECAP biomarker resulting from previous therapy adjustments for themost appropriate stimulation parameters that fit the desires of theuser. The guided algorithm may generate a low or high weighted average,a safe average that minimizes the chances of overstimulation, a trendtarget that weights more recent patient adjustments to therapy greaterthan older therapy adjustments, or even an intergroup average that looksto therapy adjustments to programs in different groups that providestimulation therapy. In any case, the user may be able to program theplurality of programs with each suggested therapy parameter with theselection of a single confirmation input.

IMD 14 may be constructed with a biocompatible housing, such as titaniumor stainless steel, or a polymeric material such as silicone orpolyurethane, and surgically implanted at a site in patient 12 near thepelvis. IMD 14 may also be implanted in patient 12 at a locationminimally noticeable to patient 12. Alternatively, IMD 14 may beexternal with percutaneously implanted leads. For SCS, IMD 14 may belocated in the lower abdomen, lower back, upper buttocks, or otherlocation to secure IMD 14. Leads 16 may be tunneled from IMD 14 throughtissue to reach the target tissue adjacent to spinal cord 18 forstimulation delivery.

At the distal tips of leads 16 are one or more electrodes that transferthe electrical stimulation from the lead to the tissue. The electrodesmay be electrode pads on a paddle lead, circular (e.g., ring) electrodessurrounding the body of leads 16, conformable electrodes, cuffelectrodes, segmented electrodes, or any other type of electrodescapable of forming unipolar, bipolar or multipolar electrodeconfigurations for therapy. The electrodes may pierce or affix directlyto the tissue itself. In general, ring electrodes arranged at differentaxial positions at the distal ends of leads 16 will be described forpurposes of illustration.

FIG. 2 is a conceptual diagram illustrating an example system 22 that isconfigured to deliver sacral neuromodulation to patient 12. As shown inFIG. 2, system 22 includes stimulator 34 (e.g., and electricalstimulator or IMD) coupled to a medical lead 36 carrying electrodes 38near a distal end of lead 36. System 22 may also include an optionalelectrode patch 44. In examples where stimulator 34 is external, lead 36may be connected to a lead extension (not shown) passing through theskin and coupled to stimulator 34. Stimulator 34 may deliver electricalstimulation at least partially defined by a set of therapy parametervalues (e.g., current amplitude, voltage amplitude, pulse width, pulsefrequency, and electrode combination). In some examples, system 22 maybe configured to provide peripheral nerve stimulation, e.g. sciaticnerve stimulation, tibibial nerve stimulation, or stimulation at asurface of a painful dermatome (e.g., low back or leg), for exampleapplied to a patient having lower back pain who have SCS therapy. Theconfiguration of system 22 for such stimulation may include location ofthe electrodes of the lead proximate to such nerves. An evoked potentialfrom the SCS lead can be captured by stimulating nerves innervating inthe low back. Therefore, this potential will be an objective readout ofpain symptom and efficacy marker. In various examples, peripheralstimulation could include other stimulation modalities in addition toelectrical stimulation, e.g., mechanical, cold, and heat stimulation.

Although a single lead 36 is shown, two or more leads may be used inother examples. For example, system 22 may include a second lead inorder to provide bilateral neuromodulation. Bilateral neuromodulationmay be provided alternatively or simultaneously depending upon thesymptoms or disease being treated. For example, a stimulation pulse maybe applied on both sides of the midline at the same time. In otherexamples, stimulation may be provided by first one lead to one side, andthen by the other lead, to the other side. In some examples, theintensities of stimulation applied by each lead or for each nerve may beadjusted individually based on an eECAP response to stimulation fromeach lead, or to each nerve.

Stimulator 34 may include a therapy delivery module and/or othercomponents configured to deliver, via lead 36 and one or more electrodes38, electrical stimulation to a sacral nerve 32 that may potentiallyprovide therapy to control fecal or urinary incontinence, for example.Fecal incontinence may refer to a condition of involuntary loss of fecalmatter, and may include urge incontinence, stress incontinence, or bothstress and urge incontinence, which may be referred to as mixedincontinence. As used in this disclosure, the term “fecal incontinence”includes disorders in which fecal matter is voided (i.e., defecation)when not desired, such as stress or urge incontinence, and disorders inwhich fecal voiding does not occur as desired, such as irritable bowelsyndrome. Urinary incontinency may refer to a condition of loss ofbladder control, and may include urge incontinence, stress incontinence,or both stress and urge incontinence, which may be referred to as mixedincontinence. As used in this disclosure, the term “urinaryincontinence” includes disorders in which urine is voided when notdesired, such as stress or urge incontinence, and disorders in whichurinary voiding does not occur as desired, such as diabetes. Similar tofecal incontinence, urinary incontinence or other pelvic floor disorders(e.g., sexual dysfunction) may also result from a lack of voluntarycontrol and may be treated with electrical stimulation, pharmaceuticals,or other therapies. In some examples where stimulator 34 is used totreat fecal incontinence, stimulation may be applied to the secondsacral nerve. In some examples where stimulator 34 is used to treaturinary incontinence, stimulation may be delivered to the third sacralnerve. Although discussed with respect to therapy for bladder and boweldysfunctions, system 22 may be used to treat other pelvic floorconditions, to provide peripheral nerve simulation for chronic pain orsexual dysfunction, or other treatments based on stimulation applied toone or more sacral nerves.

Although only two electrodes 38 are shown on lead 36, system 22 mayinclude three or more electrodes in other examples. In addition,electrodes 38 may be implantable or at least partially implantable inother examples. For example, lead 36 may be transcutaneous or electrodes38 may be part of a fully implantable device for sensing and monitoringeECAP signals. In examples, including two leads, each lead may includetwo or more electrodes. In some examples, one electrode may be used forsensing, while another is used for providing simulation. The electrodesmay be on the same lead or on different leads. Stimulation may beprovided ipsilaterally or contralaterally.

Patient 12 includes intestines 23 that may be subject to a conditionsuch as fecal incontinence. Intestines 23 may include a descendingcolon, a sigmoid colon, rectum 24 and an anus. During normal, or healthyfunction of intestines 23, the sigmoid colon and rectum 24 are depictedsuch that their position relative to one another form a “valve” or“fold” that prevents fecal matter from entering rectum 24. During afecal voiding event, however the sigmoid colon and rectum 24 may shiftto positions that open the value or fold thereby allowing fecal matterin the sigmoid colon to pass to rectum 24 and exit the anus. When fecalmatter is present in the sigmoid colon or rectum 24, patient 12 maytypically recognize the sensation and take action (e.g., prevent fecalvoiding or voluntarily void the fecal matter). However, for a patientwith fecal incontinence, patient 12 may not recognize the sensation offecal matter or be able to voluntarily control the need to void.

Although fecal incontinence may be caused by muscular or neurologicaldysfunction, sensations and stimulation of pelvic floor nerves and/orsensed eECAP signals may still be useful for identifying therapies thatmay be effective in treating the condition of patient 12. For example,eECAP signals may be detected by electrodes 38 indicating that nerves inthe area near rectum 24 are being activated by applied stimulation. Insome examples, eECAP signals may be detected during initial programmingof SNM device such as the one in system 22. For example, stimulationintensity may be slowly raised, e.g., by adjusting one or more ofvoltage or current amplitude, pulse width or pulse rate, until an eECAPbiomarker is first detected. Ongoing stimulation therapy is thenprovided by stimulator 34 at an intensity level below the level whichresulted in an eECAP biomarker. In some examples, the stimulationintensity may be set to 50%, 80%, or 90% of the stimulation intensityresulting in the eECAP biomarker, for example. If voltage or currentpulse amplitude is adjusted, for example, the amplitude may be set to50%, 80%, or 90% of the amplitude that resulted in the eECAP biomarker.

In some examples, the set of therapy parameter values selected forelectrical stimulation to treat fecal incontinence may include pulsesdelivered at a certain frequency. For example, if stimulation comprisesdelivery of pulses, the pulse frequency may be selected from a rangebetween 0.05 Hz and 50 Hz. In another example, the pulse frequency maybe selected from a range between 0.1 Hz and 25 Hz. In still anotherexample, the pulse frequency may be selected from a range between 0.5 Hzand 15 Hz. In one example, the pulse frequency may be selected frombetween approximately 1.0 and 3.0 Hz. These frequencies may elicitcortical evoked potentials and therapy related to fecal incontinence.However, these frequencies may also be effective in treating otherdisorders such as urinary incontinence or sexual dysfunction.

Stimulator 34 may also include a therapy delivery module and/or othercomponents configured to deliver, via lead 36 and one or more electrodes38, electrical stimulation to second sacral nerve 32 (i.e., S2) or othernerve that may potentially provide therapy to control the fecalincontinence of patient 12. In the example shown in FIG. 2, the distalend of lead 36 is inserted into sacral foramen 30 of sacrum 28. Sincesecond sacral nerve 32 may be known to innervate portions of intestines23 such as rectum 24, electrodes 38 may be implanted adjacent to secondsacral nerve 32 to evaluate the efficacy of therapy delivered to thissite. In this manner, the second sacral nerve 32 may be associated withthe anatomical regions of intestines 23 and rectum 24. A nerve or nerveswhich innervate or otherwise carry impulses to or away from ananatomical region may be referred to as a nerve associated with theanatomical region. In other examples, stimulation of second sacral nerve32 may be performed using electrodes external of the pelvic floor eithersubcutaneously implanted or placed on the external surface of the skin.However, these other locations may not be sufficiently precise toevaluate stimulation therapy. In some examples, stimulation may bedelivered to second sacral nerve 32 and additional nerves adjacent tothe sacral nerve. For example, stimulation may be delivered to both S2and S3 nerves.

In examples directed to treating fecal incontinence, stimulator 34 maybe configured to deliver electrical stimulation to second sacral nerve32 according to a selected set of stimulation therapy parameter values.This set of therapy parameter values may at least partially define theelectrical stimulation and include parameter values for one or moretherapy parameters such as current amplitude, voltage amplitude, pulsewidth, pulse frequency, waveform shape (in examples that includecontinuous waveform delivery) and electrode combinations. The set oftherapy parameter values may be selected according to clinicianexperience, patient condition, or any other circumstances. Fecalincontinence may also be treated by stimulating one or more other nervesin addition or alternative to second sacral nerve 32. For example,stimulation may be directed to one or more of a pelvic floor nerve, apelvic floor muscle, the anal sphincter, or other pelvic floor targets.Pelvic floor nerves include peripheral nerves such as sacral nerves,pudendal nerves and associated branches, and dorsal genital nerves.

In the example shown in FIG. 2, lead 36 is cylindrical. Electrodes 38leads 36 may be ring electrodes, segmented electrodes, or partial ringelectrodes. Segmented and partial ring electrodes each extend along anarc less than 360 degrees (e.g., 90-120 degrees) around the outerperimeter of lead 36. In some examples, lead 36 may have a complexelectrode geometry. An example of a complex electrode array geometry mayinclude an array of electrodes located at different axial positionsalong the length of a lead in addition to electrodes located atdifferent angular positions about the periphery, e.g., circumference, ofthe lead 36. In examples, lead 36 may be, at least in part,paddle-shaped (i.e., a “paddle” lead), e.g., where an array of electrodepads is provided in a two-dimensional array on a surface of the paddlelead. In some examples, one or more of electrodes 38 may be cuffelectrodes that are configured to extend at least partially around anerve (e.g., extend axially around an outer surface of a nerve).Delivering stimulation via one or more cuff electrodes and/or segmentedelectrodes may help achieve a more uniform electrical field oractivation field distribution relative to the nerve, which may helpminimize discomfort to patient 12. An electrical field represents theareas of a patient anatomical region that will be covered by anelectrical field during delivery of stimulation therapy to tissue withinpatient 12. The electrical field may define the volume of tissue that isaffected when the electrodes 38 are activated. An activation fieldrepresents the neurons that will be activated by the electrical field inthe neural tissue proximate to the activated electrodes.

Additionally, or alternatively, system 22 may be configured to controldelivery of electrical stimulation and sense eECAP biomarkers to screenfor effective therapy to treat a bladder related condition of patient12. In some examples directed to treatment of bladder relatedconditions, lead 36 may directed through sacral foramen 76 in order forstimulator 34 to deliver electrical stimulation to third sacral nerve 78via one or more electrodes 38 of lead 36. Third sacral nerve 78 mayinnervate anatomical regions associated with urinary incontinence suchas the muscular wall of bladder 40 and urinary sphincter 42. Additionalor alternative nerves may also be targeted by one or more of electrodes38.

As discussed above with respect to fecal incontinence, stimulation maybe applied to third sacral nerve 78 while a signal is monitored for aneECAP biomarker via electrodes 38. During programming, stimulationintensity may be incrementally raised until an eECAP biomarker appearsin the sensed eECAP signal. Therapeutic stimulation may be programmed tobe delivered at a percentage of the stimulation intensity which resultedin the eECAP biomarker.

In some examples, system 22 may include an electrode patch 44, or otherelectrode located in an area near the target of applied stimulation. Forexample, electrode patch may be located in an area near the rectum whensystem 22 is used to treat fecal incontinence. Electrode patch 44 maycollect a signal including an eECAP biomarker.

FIG. 3 is a functional block diagram illustrating various components ofan IMD 14. In the example of FIG. 3, IMD 14 includes a processingcircuitry 80, memory 82, stimulation generator 84, posture state module86, telemetry circuit 88, power source 90, and eECAP sensor 92. Thestimulation generator 84 forms a therapy delivery module. Memory 82 maystore instructions for execution by processing circuitry 80, stimulationtherapy data, eECAP biomarkers, posture state information, posture stateindications, and any other information regarding therapy or patient 12.Therapy information may be recorded for long-term storage and retrievalby a user, and the therapy information may include any data created byor stored in IMD 14. Memory 82 may include separate memories for storinginstructions including instructions for eECAP analysis, posture stateinformation, therapy adjustment information, prior detected eECAPbiomarkers, program histories, and any other pertinent data orinstructions.

Processing circuitry 80 controls stimulation generator 84 to deliverelectrical stimulation via electrode combinations formed by electrodesin one or more electrode arrays. For example, stimulation generator 84may deliver electrical stimulation therapy via electrodes on one or moreleads 16, e.g., as stimulation pulses or continuous waveforms.Components described as processing circuitry within IMD 14, externalprogrammer 20 or any other device described in this disclosure may eachcomprise one or more processors, such as one or more microprocessors,digital signal processors (DSPs), application specific integratedcircuits (ASICs), field programmable gate arrays (FPGAs), programmablelogic circuitry, or the like, either alone or in any suitablecombination.

Stimulation generator 84 may include stimulation generation circuitry togenerate stimulation pulses or waveforms and switching circuitry toswitch the stimulation across different electrode combinations, e.g., inresponse to control by processing circuitry 80. In particular,processing circuitry 80 may control the switching circuitry on aselective basis to cause stimulation generator 84 to deliver electricalstimulation to selected electrode combinations and to shift theelectrical stimulation to different electrode combinations in a firstdirection or a second direction when the therapy must be delivered to adifferent location within patient 12. In other examples, stimulationgenerator 84 may include multiple current sources and sinks to drivemore than one electrode combination at one time. For example, eachelectrode may have its own current source and current sink, which can beselectively activated so that the electrode can source or sinkcontrolled amounts of current. An electrode configuration, e.g.,electrode combination and associated electrode polarities, may berepresented by a data stored in a memory location, e.g., in memory 82,of IMD 14. Processing circuitry 80 may access the memory location todetermine the electrode combination and control stimulation generator 84to deliver electrical stimulation via the indicated electrodecombination. To adjust electrode combinations, amplitudes, pulse rates,or pulse widths, processing circuitry 80 may command stimulationgenerator 84 to make the appropriate changes to therapy according toinstructions within memory 82 and rewrite the memory location toindicate the changed therapy. In other examples, rather than rewriting asingle memory location, processing circuitry 80 may make use of two ormore memory locations.

When activating stimulation, processing circuitry 80 may access not onlythe memory location specifying the electrode combination but also othermemory locations specifying various stimulation parameters such asvoltage or current amplitude, pulse width and pulse rate. Stimulationgenerator 84, e.g., under control of processing circuitry 80, then makesuse of the electrode combination and parameters in formulating anddelivering the electrical stimulation to patient 12.

According to examples described herein, processing circuitry 80 mayadjust such stimulation parameters to modify stimulation therapydelivered by IMD 14 based on the detected eECAP biomarker of patient 12.In some examples, processing circuitry 80 may detect an eECAP biomarkerof patient 12 via eECAP sensor 92 that indicates that a modification ofthe stimulation therapy is appropriate, e.g., according to instructionsstored in memory 82. Processing circuitry 80 may access instructions formodifying the stimulation therapy based on the detected eECAP biomarker,e.g., by changing from the current stimulation program to a programwhich results in a desired eECAP biomarker.

According to other examples described herein, such stimulationparameters may be adjusted to modify stimulation therapy delivered byIMD 14 based on a combination of the detected eECAP biomarker and adetected posture state. In some examples, processing circuitry 80 maydetect an eECAP biomarker of patient 12 via eECAP sensor 92 as well as aposture state of patient 12 via posture state module 86. If a change ineECAP biomarker has been detected, a detected posture state may be usedto help processing circuitry 80 determine the appropriate stimulationprogram in order to achieve a desired eECAP biomarker. For example,memory 82 may include a stimulation program associated with the detectedposture state which resulted in the desired eECAP biomarker in the past.

An exemplary range of electrical stimulation parameters likely to beeffective in treating chronic pain, e.g., when applied to spinal cord18, are listed below. However, other parameter values are contemplated.While stimulation pulses are described, stimulation signals may be ofany of a variety of forms such as sine waves or the like.

Pulse Rate: between approximately 0.5 Hz and 15 kHz, more preferablybetween approximately 5 Hz and 250 Hz, and still more preferably betweenapproximately 30 Hz and 130 Hz.

Amplitude: between approximately 0.05 volts and 50 volts, morepreferably between approximately 0.1 volts and 20 volts, and still morepreferably between approximately 1 volt and 10 volts. In otherembodiments, a current amplitude may be defined as the biological loadin the voltage that is delivered. For example, the range of currentamplitude may be between 0.1 milliamps (mA) and 50 mA.

Pulse Width: between about 10 microseconds and 5000 microseconds, morepreferably between approximately 100 microseconds and 1000 microseconds,and still more preferably between approximately 180 microseconds and 450microseconds.

In other applications, different ranges of parameter values may be used.For deep brain stimulation (DBS), as one example, alleviation orreduction of symptoms associated with Parkinson's disease, essentialtremor, epilepsy or other disorders may make use of stimulation having apulse rate in the range of approximately 0.5 to 1200 Hz, more preferably5 to 250 Hz, and still more preferably 30 to 185 Hz, and a pulse widthin the range of approximately 10 microseconds and 5000 microseconds,more preferably between approximately 60 microseconds and 1000microseconds, still more preferably between approximately 60microseconds and 450 microseconds, and even more preferably betweenapproximately 60 microseconds and 150 microseconds. Amplitude rangessuch as those described above with reference to SCS, or other amplituderanges, may be used for different DBS applications. Parameter valuesother than those described above are contemplated.

Processing circuitry 80 accesses stimulation parameters in memory 82,e.g., as programs and groups of programs. Upon selection of a particularprogram group, processing circuitry 80 may control stimulation generator84 to deliver stimulation according to the programs in the groups, e.g.,simultaneously or on a time-interleaved basis. A group may include asingle program or multiple programs. As mentioned previously, eachprogram may specify a set of stimulation parameters, such as amplitude,pulse width and pulse rate. In addition, each program may specify aparticular electrode combination for delivery of stimulation. Again, theelectrode combination may specify particular electrodes in a singlearray or multiple arrays, e.g., on a single lead or among multipleleads. Processing circuitry 80 also may control telemetry circuit 88 tosend and receive information to and from external programmer 20. Forexample, telemetry circuit 88 may send information to and receiveinformation from programmer 20.

In some examples, IMD 14 includes a posture state module 86 which allowsIMD 14 to sense or detect the current patient posture state, e.g.,posture, activity or any other static position or motion of patient 12.In the example of FIG. 2, posture state module 86 may include one ormore accelerometers, such as three-axis accelerometers, capable ofdetecting static orientation or vectors in three-dimensions. Thethree-axis accelerometer may be a micro-electro-mechanicalaccelerometer. In other examples, posture state module 86 mayalternatively or additionally include one or more gyroscopes, pressuretransducers or other sensors to sense the current posture state occupiedby patient 12. Posture state information generated by posture statemodule 86 and processing circuitry 80 may correspond to an activityand/or posture undertaken by patient 12 or a gross level of physicalactivity, e.g., activity counts based on footfalls or the like.

Posture state information from posture state module 86 may be stored inmemory 82 for later review by a clinician, used to adjust therapy,present a posture state indication to patient 12 and/or clinician, e.g.,via user interface display of external programmer 20, or somecombination thereof. As an example, processing circuitry 80 may recordthe posture state parameter value, or output, of the 3-axisaccelerometer and assign the posture state parameter value to a certainpredefined posture indicated by the posture state parameter value. Inthis manner, IMD 14 may be able to track how often patient 12 remainswithin a certain posture state. IMD 14 may also store which group orprogram was being used to deliver therapy when patient 12 was in thesensed posture state. Further, processing circuitry 80 may also adjusttherapy for a new posture state when posture state module 86 indicatesthat patient 12 has in fact changed postures. In some examples, thechange in posture may trigger sensing of eECAP. Based on the sensedeECAP from eECAP sensor 92, processing circuitry 80 may determine anappropriate adjustment to one or more current stimulation therapyparameters in order to achieve a desired eECAP biomarker. In someexamples, a current eECAP biomarker may be compared to an eECAP templatecorresponding to efficacious therapy.

Therefore, IMD 14 may be configured to provide eECAP responsivestimulation therapy to patient 12. Stimulation adjustments in responseto changes in eECAP biomarker or to patient state may be automatic orsemi-automatic (subject to patient approval). In many cases, fullyautomatic adjustments may be desirable so that IMD 14 may react morequickly to changes in patient state, or changes in therapy efficacy thatmay be unrelated to a change in patient state. In some examples, eECAPsensing and analysis may be used to refine stimulation therapy programsselected based on sensed posture.

Memory 82 may include definitions for each posture state of patient 12.In one example, the definitions of each posture state may be illustratedas a cone in three-dimensional space. Whenever the posture stateparameter value, e.g., a vector, from the three-axis accelerometer ofposture state module 86 resides within a predefined cone or volume,processing circuitry 80 indicates that patient 12 is in the posturestate of the cone or volume. In other examples, a posture stateparameter value from the 3-axis accelerometer may be compared to valuesin a look-up table or equation to determine the posture state in whichpatient 12 currently resides. Examples techniques for detecting apatient posture state include examples described in U.S. Pat. No.8,708,934, titled “REORIENTATION OF PATIENT POSTURE STATES FORPOSTURE-RESPONSIVE THERAPY,” filed Apr. 30, 2009 and issued Apr. 29,2014, the entire content of which is incorporated by reference herein.

Adjustments to one or more stimulation parameters responsive to changesin sensed eECAP may allow IMD 14 to implement a certain level ofautomation in therapy adjustments. In particular, IMD 14 maycontinuously, or on a periodic basis, adjust stimulation therapyparameters in order to maintain an eECAP biomarker that corresponds toefficacious treatment. Automatically adjusting stimulation may freepatient 12 from the constant task of manually adjusting therapy eachtime patient 12 changes posture. Automatically adjusting stimulationbased on sensed eECAP may also correct for natural drift of leads 16irrespective of posture state. For example, by detecting eECAPbiomarkers over time, processing circuitry 80 may determine that thelocation of the nerves being stimulated has changed over time. Suchmanual adjustment of stimulation parameters can be tedious, requiringpatient 12 to, for example, depress one or more keys of programmer 20multiple times during the patient posture state to maintain adequatesymptom control. In some embodiments, patient 12 may eventually be ableto enjoy eECAP responsive stimulation therapy, which adjusts therapyaccording to changing conditions without the need to continue makingchanges for different patient states via programmer 20. Instead, patient12 may transition immediately or over time to fully automaticadjustments based on eECAP biomarker alone or in combination withdetected patient states such as posture.

Although posture state module 86 is described as containing the 3-axisaccelerometer, posture state module 86 may contain multiple single-axisaccelerometers, dual-axis accelerometers, 3-axis accelerometers, or somecombination thereof. In some examples, an accelerometer or other sensormay be located within or on IMD 14, on one of leads 16 (e.g., at thedistal tip or at an intermediate position), an additional sensor leadpositioned somewhere within patient 12, within an independentimplantable sensor, or even worn on patient 12. For example, one or moremicrosensors may be implanted within patient 12 to communicate posturestate information wirelessly to IMD 14. In this manner, the patient 12posture state may be determined from multiple activity sensors placed atvarious locations on or within the body of patient 12.

In some examples, posture state module 86 may additionally oralternatively be configured to sense one or more physiologicalparameters of patient 12. For example, physiological parameters mayinclude heart rate, electromyography (EMG), an electroencephalogram(EEG), an electrocardiogram (ECG), temperature, respiration rate, or pH.These physiological parameters may be used by processing circuitry 80,in some embodiments, to confirm or reject changes in sensed posturestate that may result from vibration, patient travel (e.g., in anaircraft, car or train), or some other false positive of posture state.In some examples, the one or more physiological parameters may be usedto determine a patient state other than posture. In addition, eECAPsensing and analysis may be used to confirm a change in the relationshipbetween the stimulation source and stimulation target within patient 12.

In addition, IMD 14 may store patient 12 input regarding perceivedphysiological conditions (e.g., symptoms) not detectable by anyimplemented sensors. For example, patient 12 may provide input toprogrammer 20 that indicates where the patient perceives any symptomsand characteristics of that particular type of symptom. processingcircuitry 80 may associate this physiological condition information withthe currently detected posture state, the stimulation parameters, and/ora time stamp to provide a complete therapy picture to the patient orclinician at a later time. Such information may be stored in memory 82of IMD 14, the memory of programmer 20, and/or the memory of some otherdevice.

Wireless telemetry in IMD 14 with external programmer 20, e.g., apatient programmer or a clinician programmer, or another device may beaccomplished by radio frequency (RF) communication or proximal inductiveinteraction of IMD 14 with external programmer 20. Telemetry circuit 88may send information to and receive information from external programmer20 on a continuous basis, at periodic intervals, at non-periodicintervals, or upon request from the stimulator or programmer. Further,telemetry circuit 88 may transmit information, e.g., eECAP biomarkerdata, in real-time when communicating to an external device. For eECAPdata sent in real-time, telemetry circuit 88 may send the most recentlydetected eECAP biomarker or a rolling average eECAP biomarker at arelative high frequency, e.g., at or near the fastest rate supported bythe telemetry circuit. As described above, in some examples, raw signalinformation from eECAP sensor 92 may be transmitted to an externaldevice for analysis by the external device to determine the eECAPbiomarker of patient 12. To support RF communication, telemetry circuit88 may include appropriate electronic components, such as amplifiers,filters, mixers, encoders, decoders, and the like.

When an eECAP parameter value indicates that the stimulation programadministered to patient 12 has changed efficacy, processing circuitry 80may communicate with programmer 20 via telemetry circuitry 88 toindicate the newly detected change in eECAP biomarker, i.e., a new eECAPbiomarker that indicates the current efficacy of the stimulation beingprovided to patient 12. Alternatively, processing circuitry 80 mayperiodically or non-periodically send eECAP biomarker information toprogrammer 20 either unilaterally or in response to a request fromprogrammer 20. For example, programmer 20 may request the most currenteECAP biomarker, and transmit changes in stimulation parameter valuesback to IMD 14 based on analysis of the most current eECAP biomarker.

Power source 90 delivers operating power to the components of IMD 14.Power source 90 may include a small rechargeable or non-rechargeablebattery and a power generation circuit to produce the operating power.Recharging may be accomplished through proximal inductive interactionbetween an external charger and an inductive charging coil within IMD14. In some embodiments, power requirements may be small enough to allowIMD 14 to utilize patient motion and implement a kineticenergy-scavenging device to trickle charge a rechargeable battery. Inother embodiments, traditional batteries may be used for a limitedperiod of time. As a further alternative, an external inductive powersupply could transcutaneously power IMD 14 when needed or desired.

The eECAP sensor 92 detects eECAP signals. In some examples, eECAPsensor 92 may be located on lead 16, and may include for, example, oneor more of the electrodes in leads 16 in combination with suitableamplification, filtering and/or signal processing circuitry. In someexamples, eECAP sensor 92 may include additional electrode on thehousing of IMD 14. In some examples, eECAP sensor 92 may be carried byan additional sensor lead positioned somewhere within patient 12,provided as an independent implantable sensor, or even worn on patient12. For example, one or more microsensors may be implanted withinpatient 12 to communicate sensed eECAP biomarkers wirelessly to IMD 14.In this manner the eECAP sensed responses may be obtained independent ofthe location of the electrodes delivering electrical stimulationtherapy.

FIG. 4 is a functional block diagram illustrating various components ofan external programmer 20 for IMD 14. As shown in FIG. 4, externalprogrammer 20 is an external device that includes processing circuitry104, memory 108, telemetry circuit 110, user interface 106, and powersource 112. External programmer 20 may be embodied as a patientprogrammer or a clinician programmer. A clinician or patient 12interacts with user interface 106 in order to manually change thestimulation parameters of a program, change programs within a group,turn eECAP responsive stimulation ON or OFF, view therapy information,view patient state information, view a posture state indication, orotherwise communicate with IMD 14.

User interface 106 may include a screen and one or more input buttons,as in the example of a programmer, that allow external programmer 20 toreceive input from a user. Alternatively, user interface 106 mayadditionally or only utilize a touch screen display, as in the exampleof a clinician programmer. The screen may be a liquid crystal display(LCD), dot matrix display, organic light-emitting diode (OLED) display,touch screen, or any other device capable of delivering and/or acceptinginformation. For visible posture state indications, a display screen maysuffice. For audible and/or tactile posture state indications,programmer 20 may further include one or more audio speakers, voicesynthesizer chips, piezoelectric buzzers, or the like. Input buttons foruser interface 106 may include a touch pad, increase and decreasebuttons, emergency shut off button, and other buttons to control thestimulation therapy, as described above with regard to programmer 20.Processing circuitry 104 controls user interface 106, retrieves datafrom memory 108 and stores data within memory 108. Processing circuitry104 also controls the transmission of data through telemetry circuit 110to IMDs 14 or 26. Memory 108 includes operation instructions forprocessing circuitry 104 and data related to patient 12 therapy.

Telemetry circuit 110 allows the transfer of data to and from IMD 14, orIMD 26. Telemetry circuit 110 may communicate automatically with IMD 14in real-time, at a scheduled time, or when the telemetry circuit detectsthe proximity of the stimulator. User interface 106 may then updatedisplayed information accordingly. Alternatively, telemetry circuit 110may communicate with IMD 14 when signaled by a user through userinterface 106. To support RF communication, telemetry circuit 110 mayinclude appropriate electronic components, such as amplifiers, filters,mixers, encoders, decoders, and the like. Power source 112 may be arechargeable battery, such as a lithium ion or nickel metal hydridebattery. Other rechargeable or conventional batteries may also be used.In some cases, external programmer 20 may be used when coupled to analternating current (AC) outlet, i.e., AC line power, either directly orvia an AC/DC adapter.

In some examples, external programmer 20 may be configured to rechargeIMD 14 in addition to programming IMD 14. Alternatively, a rechargingdevice may be capable of communication with IMD 14. Then, the rechargingdevice may be able to transfer programming information, data, or anyother information described herein to IMD 14. In this manner, therecharging device may be able to act as an intermediary communicationdevice between external programmer 20 and IMD 14. In other cases, theprogrammer may be integrated with a recharging functionality in thecombined programming/recharging device. The techniques described hereinmay be communicated between IMD 14 via any type of external devicecapable of communication with IMD 14.

FIG. 5 is a block diagram illustrating an example system 120 thatincludes an external device, such as a server 122, and one or morecomputing devices 124A-124N, that are coupled to IMD 14 and externalprogrammer 20 shown in FIG. 1 via a network 126. In this example, IMD 14may use its telemetry circuit 88 to communicate with external programmer20 via a first wireless connection, and to communication with an accesspoint 128 via a second wireless connection.

In the example of FIG. 5, access point 128, external programmer 20,server 122, and computing devices 124A-124N are interconnected, and ableto communicate with each other, through network 126. In some cases, oneor more of access point 128, external programmer 20, server 122, andcomputing devices 124A-124N may be coupled to network 126 through one ormore wireless connections. IMD 14, external programmer 20, server 122,and computing devices 124A-124N may each comprise one or moreprocessors, such as one or more microprocessors, digital signalprocessors (DSPs), application specific integrated circuits (ASICs),field programmable gate arrays (FPGAs), programmable logic circuitry, orthe like, that may perform various functions and operations, such asthose described in this disclosure.

Access point 128 may comprise a device, such as a home monitoringdevice, that connects to network 126 via any of a variety ofconnections, such as telephone dial-up, digital subscriber line (DSL),or cable modem connections. In other embodiments, access point 128 maybe coupled to network 126 through different forms of connections,including wired or wireless connections.

During operation, IMD 14 may collect and store various forms of data.For example, IMD 14 may collect sensed eECAP biomarkers and posturestate information during therapy that indicate how patient 12 movesthroughout each day, and movement of leads 16 with respect to thestimulation target. In some cases, IMD 14 may directly analyze thecollected data to evaluate efficacy of adjustments to stimulationtherapy based sensed patient posture. In other cases, however, IMD 14may send stored data relating to posture state information and sensedeECAP biomarker to external programmer 20 and/or server 122, eitherwirelessly or via access point 128 and network 126, for remoteprocessing and analysis.

For example, IMD 14 may sense, process, trend and evaluate the sensedeECAP response, posture state information, and other therapyinformation. This communication may occur in real time, and network 126may allow a remote clinician to review the current patient posture stateby receiving a presentation of a posture state indication along withother therapy information on a remote display, e.g., computing device124A. Alternatively, processing, trending and evaluation functions maybe distributed to other devices such as external programmer 20 or server122, which are coupled to network 126. In addition, posture stateinformation and other therapy information may be archived by any of suchdevices, e.g., for later retrieval and analysis by a clinician. Forexample, the archived therapy information may be presented to a user viauser interface 106 (FIG. 3).

In some cases, IMD 14, external programmer 20 or server 122 may processposture state information, eECAP biomarker, or raw data and/or therapyinformation into a displayable eECAP biomarker report, which may bedisplayed via external programmer 20 or one of computing devices124A-124N. The eECAP report may contain trend data for evaluation by aclinician, e.g., by visual inspection of graphic data. In some cases,the eECAP report may include the number of activities patient 12conducted, a percentage of time patient 12 was in each posture state,how magnitude in change to the eECAP biomarker for a particular changein posture, what group or program was being used to deliver therapyduring each activity, the number of manual adjustments to therapyprovided in addition to eECAP responsive adjustments, or any otherinformation relevant to patient 12 therapy, based on analysis andevaluation performed automatically by IMD 14, external programmer 20 orserver 122. A clinician or other trained professional may review thehistorical therapy information including the stimulation parameters,physiological conditions, and changes in eECAP in response tostimulation to possibly identify any problems or issues with the therapythat should be addressed.

In addition, network 126 may be configured to facilitate real-timecommunication between IMD 14 and computing device 124A for programmingbased on a currently sensed eECAP biomarker. Although there may be someslight delay in the transfer of information, this may still beconsidered real-time programming utilizing any user interface such asuser interfaces 200, 270, or 290. The clinician may be able to remotelyvisit with patient 12, review stored therapy information, and make anyprogramming changes in real-time using system 120.

In some cases, server 122 may be configured to provide a secure storagesite for archival of eECAP biomarker and patient state information thathas been collected from IMD 14 and/or external programmer 20. Network126 may comprise a local area network, wide area network, or globalnetwork, such as the Internet. In other cases, external programmer 20 orserver 122 may assemble posture state information in web pages or otherdocuments for viewing by trained professionals, such as clinicians, viaviewing terminals associated with computing devices 124A-124N. System120 may be implemented, in some aspects, with general network technologyand functionality similar to that provided by the Medtronic CareLink®Network developed by Medtronic, Inc., of Minneapolis, Minn.

Although some examples of the disclosure may involve eECAP biomarkers,posture state information and related data, system 120 may be employedto distribute any information relating to the treatment of patient 12and the operation of any device associated therewith. For example,system 120 may allow therapy errors or device errors to be immediatelyreported to the clinician. In addition, system 120 may allow theclinician to remotely intervene in the therapy and reprogram IMD 14,programmer 20, or communicate with patient 12. In an additional example,the clinician may utilize system 120 to monitor multiple patients andshare data with other clinicians in an effort to coordinate rapidevolution of effective treatment of patients. Further, eECAP biomarkerdetection may be used to provide notifications, such as providingnotification via a wireless link to a care giver a lead has shiftedsubstantially.

Furthermore, although the disclosure is described with respect to SCStherapy, such techniques may be applicable to IMDs that convey othertherapies the relationship between lead 16 and the target stimulationlocation may change, such as, e.g., DBS, pelvic floor stimulation,gastric stimulation, occipital stimulation, functional electricalstimulation, and the like.

As described above, in some examples, an external device, such as, e.g.,external programmer 20 may present therapy information to a user via auser interface. The therapy information presented to a user may relateto therapy delivered to a patient by IMD 14 or some other medicaldevice. The therapy information presented by the external device mayinclude eECAP biomarker, patient posture state information,physiological therapy information, and therapy parameter information.

The therapy parameter information and physiological therapy informationmay be associated with a particular eECAP biomarker. In some examples,the information may also be associated with patient posture stateinformation. The same eECAP biomarker may be associated with more thanone patient posture state. For example, the therapy parameterinformation presented to a user may include an indicator of one or moretherapy parameters programmed for delivery for a particular eECAPbiomarker or particular patient posture state indicated to the user bythe user interface. In some examples, the therapy parameter informationmay include an indicator of previous adjustments made by a user to oneor more therapy parameters for therapy delivered to a patient in orderto achieve a desired eECAP biomarker associated with efficacioustherapy. In the case of physiological condition information,physiological conditions associated with patient posture stateinformation may include physiological symptoms experienced by thepatient when in a particular posture state.

The user interface of an external device may be configured to receivefeedback from a user (e.g., a patient or clinician) regardingphysiological conditions information and/or the therapy parameterinformation associated with patient posture state information. In oneexample, the external device including the user interface for presentingtherapy information may receive one or more therapy parameters for thetherapy associated with a specific posture state of the patient. Suchtherapy parameter adjustments may be communicated to IMD 14 or otherdevice for delivering therapy to patient 12 for the associated posturestate. In another example, the external device including the userinterface for presenting the therapy information may receive inputregarding one or more physiological conditions indicated by a patientfor a particular posture state. The therapy information presented to auser may be updated based on the input received from a user via the userinterface.

FIG. 6 illustrates a pair of graphs 150, 160, each graph illustrating astimulation pulse, and the sensed eECAP signal generated in response tothe stimulation pulse, respectively. Prior to the collection of thetraces shown in graphs 150 and 160, the lumbar spine being monitored forthe eECAP signal was bursted with stimulation therapy provided at afrequency of 10 kHz for one minute. Recording of the eECAP is notfeasible during the 10 kHz high frequency burst owing to stimulationartifacts obscuring the neural response. A slower stimulation frequency,in this case, a 10 Hz stimulation pulse, provides ample opportunity togenerate the eECAP after the slower frequency stimulation pulse isdelivered with no corruption from the stimulation artifact. Although 10Hz was used to elicit the eECAP in this particular example, otherfrequencies both faster and slower such as those between about 1 Hz and500 Hz, between 2 Hz and 250 Hz and about 50 Hz are also contemplatedfor use in providing low frequency stimulation.

As illustrated in graph 150, an electrical stimulation signal 157including a stimulation pulse 158, as generally indicated by bracket152, is applied to the spine of a sheep (test patient) with a MedtronicModel 3778 1×8 Compact Percutaneous Lead. The electrical stimulationsignal 157 comprises a stimulation pulse having parameters of 5Vbiphasic, applied at frequency of 10 Hz for 60 μs, delivered with aMedtronic Model 39565 lead in the mid-lumbar spine. The stimulationpulse 158 is delivered 0.1 seconds after cessation of the 10 kHz highfrequency burst and in this example is delivered continuously for a timeperiod after cessation of the high frequency stimulation. The eECAPsignal 153 sensed in response to the stimulation pulse 158 is generallyindicated by bracket 151. The sensed eECAP signal 153 includes a pulse154 that was sensed during a time when the stimulation pulse 158 wasbeing applied to the test patient. The sensed eECAP signal also includesa first peak 155 attributed to nerve firing of the Aα Type I fibers, anda second (later in time) peak 156 attributed to nerve firing of Aα TypeII fibers.

As illustrated in graph 160, an electrical stimulation signal 167includes a stimulation pulse 168, as generally indicated by bracket 162,is applied to the spine of the sheep (test patient) in a same manner asdescribed above, using the same parameters (5V biphasic, applied atfrequency of 10 Hz for 60 μs), and using the same lead and same sensingelectrodes as described above for electrical stimulation signal 157,except that stimulation signal 167 is applied 27 seconds after cessationof the 10 kHz stimulation instead of the 0.1 second delay used in theapplication of stimulation signal 157. The eECAP signal 163 sensed inresponse to the stimulation pulse 168 is generally indicated by bracket161. The sensed eECAP signal 163 includes a pulse 164 that was sensedduring a time when the stimulation pulse 168 was being applied to thetest patient. The sensed eECAP signal also includes a peak 165. Asillustrated by eECAP signal 163, the effect of the high-frequencystimulation (10 kHz one-minute burst) has washed out, and only a singlepeak is evident in the eECAP associated with nerve firing of the Aα TypeI fibers, wherein any contribution to the eECAP signal generated by thenerve firing of Aα Type II fibers is masked by the much larger Aα Type IeECAP. In some examples, the level of stimulation provided by pules 158,168 may be below the level that is perceptible to a patient, such as ahuman patient. In other examples, the level of stimulation provided bypulses 158, 168 is above the level that is perceptible to a patient,such as a human patient. The peak amplitudes of the Aα Type I and TypeII eECAP signals after cessation of the 10 kHz burst as a function oftime are further illustrated and described below with respect to FIG. 7.Although shown as a “ping” or a pulse in FIG. 6, the low frequencystimulation may be delivered continuously beginning immediately aftercessation of the application of the high frequency burst, and deliveredfor some predefined period of time, such as 30 seconds. During the timeof application of the low frequency stimulation, the eECAP is capable ofbeing measured, either continuously, or at some predetermined samplerate, to sense the eECAP signals referred to herein.

FIG. 7 illustrates a graph 170 of peak amplitudes of an eECAP signal forAα Type I nerve fibers and for Aα Type II nerve fibers after cessationof an applied burst of electrical stimulation as a function of time. Theapplied burst of electrical stimulation is a same 10 kHz burst ofstimulation, applied to the spine of the sheep (test patient) is themanner described above with respect to FIG. 6. The plot of the eECAP forboth the Aα Type I nerve fibers and for Aα Type II nerve fibers as shownin FIG. 7 is derived from plots from the eECAP signals 153 and 163 asillustrated and described above with respect to FIG. 6.

As shown in FIG. 7, graph 170 comprises a vertical axis representing theeECAP amplitude of the signals in volts, and a horizontal axisrepresenting time in seconds after cessation of the 10 kHz therapysignal. The zero-point origin along the horizontal axis of graph 170represents the time of cessation of the 10 kHz stimulation, and the timeto the right along the horizontal axis represents the number of secondsfollowing the cessation of the 10 kHz stimulation burst. Graph 170includes a trace 171 illustrating the peak amplitudes of the eECAPsignal associated with the Aα Type I nerve fibers following cessation ofthe 10 kHz burst, and a trace 172 illustrating the peak amplitudes ofthe eECAP signal associated with the Aα Type II nerve fibers followingcessation of the same 10 kHz burst. Graph 170 also illustrates a trace173 representative of a least squares fit to the Aα Type I data of trace171 of the form OFFSET+(eECAP Initial Value)*(1−e{circumflex over( )}(−t/τ)). While the eECAP amplitude was assessed for each of thefiber types in graph 170, other assessments of the eECAP signalassociated with the integral, power, or area under the curve could beused interchangeably for analysis of the eECAP traces and for comparisonpurposes between the signals associated with the Aα Type I and the AαType II nerve fibers.

As illustrated in FIG. 7, the amplitude (i.e., the magnitude of thevoltage) represented by the vertical axis of graph 170 represents thelevel of nerve firing provided by the respective nerve fibers to apatient's brain. The higher the voltage level of the trace, the morenerve firings, and in general the more indication of a sensation of painis being sent through the spinal column of the patient. The applicationof the 10 kHz burst of stimulation therapy may be intended to drive downthe amplitudes (level of nerve firing activity) being sent through thespinal column, and modulate the perception of pain experienced by thepatient receiving the stimulation therapy. As shown in Graph 170, at thetime of cessation of the 10 kHz burst of stimulation, the amplitude ofthe eECAP signals for the Aα Type I nerve fibers has an initial value174 at time zero of approximately 10 μV. The amplitude of the eECAPsignal associated with the Aα Type II nerve fibers has nearly a same orslightly higher initial value 175. As shown by trace 172, the amplitudevalue of the eECAP associated with the Aα Type II nerve fibers variesbetween approximately 15 and 9 μV, wherein the masking of the Aα Type IIeECAP is complete in a time period 178 of about eight seconds after the10 kHz burst terminates. As shown by trace 171, the amplitude value ofthe eECAP associated with the Aα Type I nerve fibers begins at aninitial (offset) value of approximately 10 μV, but in view of the fittedcurve of trace 173, increases in magnitude after cessation of the 10 kHzburst in somewhat of an exponential-shaped curve. After a first timeperiod 176 following cessation of the 10 kHz burst, (i.e., 10 seconds),the amplitude of fitted trace 173 has risen to a value just over 30 μV,and after a second time period 177 following cessation of the 10 kHzstimulation (i.e., 20 seconds), the amplitude of the fitted trace 173has continued to rise to a value just under 40 μV.

Based on the traces 153, 163 of the eECAP signals as provided in FIG. 6,and/or the plots of the eECAP amplitudes represented by traces 171, 172,173 shown in FIG. 7, various parameters may be directly measured fromthese traces, and/or derived from measurements taken from these traces,or other types of traces the could be derived from the eECAP signals asmentioned above. Example parameters of interest which may be extractedfrom the eECAP following a specific therapeutic or diagnosticintervention may include, but are not limited to:

-   -   Fiber latency (relative to the stimulation pulse)—in some        examples represented by a time between stimulation pulse and the        peak of the resulting eECAP signal.    -   Time to specific fiber type masking—in some examples the time        may be determined when a particular ratio is achieved between        the value of one eECAP signal generated by a particular type of        nerve fiber exceeds a threshold ratio of an eECAP signal        generated by a different particular type of nerve fiber    -   eECAP width—in some examples, a width (in time) of some portion        of an eECAP signal bounded by some redeemed threshold values for        the waveform    -   eECAP amplitude, area under the curve, power or integral offset    -   eECAP amplitude, area under the curve, power or integral initial        value    -   eECAP recovery time constant        Also additional parameters may be derived parameters based on        the eECAP signals such as but not limited to:    -   Ratio of eECAP amplitude, area under the curve, or power for one        fiber type versus that of another.    -   Difference in fiber latency for one fiber type with respect to        another.

As further described below, one or a combination of these parameters maybe used to compare one sensed eECAP signal to another eECAP signal, orto compare a sensed eECAP signal to a target eECAP for the purposes ofevaluating the applied stimulation therapies that generated the eECAPsignal against one another. Thus, the eECAP signal and the associatedparameters of the eECAP signals provide a tool to determine relativeefficacies of the stimulation therapies for a patient, and/or relativesystem performance features of the systems providing the stimulationtherapies, such as IMD 14, while providing stimulation therapies basedon different therapy parameters.

For example, the initial value 174 for the Aα Type I nerve fibers ofapproximately 10 μV may be used as a baseline value for this eECAPparameter. Another eECAP signal may be are sensed that was generated byapplying a candidate therapy, the candidate therapy utilizing a set oftherapy parameters that was different in at least one therapy parametervalue than was used in the stimulation therapy that generated thebaseline eECAP. By comparing the initial value measured for the Aα TypeI nerve fiber response of the candidate therapy to the initial value 174of the baseline eECAP, a determination can be made as to whether theeECAP generated by the candidate therapy is different from or isequivalent to the baseline eECAP. For example, the eECAP generated bythe candidate therapy may be considered “different from” the baselineeECAP if the initial value measured for the eECAP generated by thecandidate therapy exceeds the initial value 174, (e.g., exceeds 10 μv),and may be considered “equivalent to” the baseline eECAP if the initialvalue for the eECAP generated by the candidate therapy is less than orequal to the initial value 174 of the baseline eECAP.

In another example, the eECAP generated by the candidate therapy may beconsidered to “match” to a target eECAP if the initial value measuredfor the eECAP generated by the candidate therapy falls within a range ofvalues that includes or is based on initial value 174. For example, if ameasured initial value of the eECAP for the Aα Type 1 nerve fibersgenerated by the candidate therapy is measured and is determined to fallwithin ±0.5V of the initial value 174 determined for the baseline eECAP,then the eECAP signal associated with the candidate therapy may beconsidered to be a “match” for the baseline eECAP. Comparisons of theinitial values as described above are not limited to an initial valueassociated with a particular type of nerve fiber, and may be performedwith respect to any type of nerve fiber generating an eECAP response,and the comparisons in some examples is made between correspondinginitial values for two or more different nerve fiber types to determinewhether the eECAP signals are different or equivalent of one anotherand/or are a match to a target eECAP.

In another example of eECAP signal parameters that may be used tocompare a baseline eECAP signal to an eECAP generated by a candidatetherapy, a measured value at some predetermined time following cessationof the 10 kHz stimulation, or cessation of some other stimulationtherapy, may be compared. For example, as shown in graph 170 a value ofthe eECAP signal after time period 176 of 10 seconds is approximately30.5 μV. This value can be stored as a baseline value for this eECAPparameter, and a corresponding measurement at the 10-second mark can betaken from an eECAP signal generated in response to an applied candidatetherapy. The value of the eECAP generated in response to the candidatetherapy at the 10-second mark can be compared to the baseline 30.5 μVvalue, or to a range of values determined based on the 30.5 μV baselinevalue. Based on that comparison, a determination can be made as towhether the eECAP generated in response to the candidate therapy isdifferent from or equivalent to the baseline eECAP, or for example is a“match” to the baseline eECAP. The time period used for the measurementof the eECAP value is not limited to any particular time frame, and forexample may be a different time period 177 comprising a 20 second timeperiod. In some examples, comparison of more than one set of valuesmeasured after predetermined time period 176, 177 may be used to compareeECAP generated by the candidate therapy to the baseline eECAP.

In another example of a parameter that may be used to compare eECAPsignals, change in the value of the eECAP signal over a predeterminedtime period may be used. For example, the difference between the valueof the eECAP signal at the end of time period 176 may be subtracted fromthe value of the eECAP signal at the end of time period 177 to generateda delta (change in value) parameter for the eECAP signal over the periodof time between the end of time period 176 and the end of time period177. For example, the value of the eECAP signal as shown in graph 170 atthe end of time period 177 is approximately 39.5 μV, and the value atthe end of time period 176 is approximately 30.5 μV. The delta value istherefore calculated to be approximately 9.0 μV. This 9.0 μV value maybe used as the baseline value for this parameter, and the eECAP signalgenerated of the candidate therapy may be analyzed to determine thedelta value for this parameter of the eECAP as generated by thecandidate therapy. The generated delta value for the eECAP signal of thecandidate therapy may be compared to the baseline value for this sameparameter, as described above, to determine whether the eECAP signal isdifferent from or equivalent to, and/or is a match for the baselineeECAP.

In another example of a parameter that may be measured from the graph170, a time period 178 can be taken relative to trace 172, time period178 a measurement of the time from cessation of the 10 kHz burst untilthe masking of the eECAP signal represented by nerve firing of the AαType II nerve fibers. The value determined for time period 178 is anexample of a parameter that may be used to classify the eECAP signalthat provided trace 172. For example, the value determined for timeperiod 178 can be compared to the value for this same eECAP signaldetermined for a baseline eECAP signal, and if the value of time period178 is within a predefined range of values for this same parameter ofthe baseline, the signal represented by trace 172 may be classified as amatch, or as equivalent to (i.e., is not different from) the baselinesignal. In an alternate example, the value of this same parameter forthe baseline may be considered to be a threshold values, and for examplethe signal represented by trace 172 may be classified as eitherexceeding this threshold (e.g., time period 178 is greater than the timeperiod corresponding to this same parameter for the baseline signal) ifthe value of time period 178 exceed the value of the baseline signal, ornot exceeding this threshold (e.g., time period 178 is less than thetime period corresponding to this same parameter for the baselinesignal) if the value of time period 178 does not exceed this thresholdvalue of the baseline signal. If the value of time period 178 for aparticular eECAP signal does not exceed the value for this parameter ofthe baseline signal, the eECAP associated with the candidate therapy isclassified as being equivalent to the baseline signal, and if the valueof time period for the particular eECAP signal does exceed the value ofthis parameter for the baseline signal, the particular eECAP signal isclassified as different from the baseline. Thus, the value measured fortime period 178 is an example of a parameter associated with an eECAPsignal that may be used to classified the eECAP response associated withthe signal.

As would be understood by one of ordinary skill in the art, the aboveprovided examples of parameters used to compare eECAP signals areillustration, and intended to be non-limiting examples. Many otherpossibilities exist for parameters that may be either directly measuredfrom or derived from an eECAP signal, and are contemplated for use bythe systems, devices, and method described in this disclosure for use incomparing eECAP signals. In addition, use of parameters associated witheECAP signals for comparison of eECAP signals is not limited to use of asingle parameter in making the determination that two or more eECAPsignal may be different or equivalent to each other, or are a match whencompared to each other. In various examples, multiple parameters may becompared between different eECAP signals in making these determinationsrelated to equivalency or/or matching between eECAP signals. Additionalexamples of various parameters that may be determined using analysis ofparameters associated with eECAP signal(s) are illustrated with respectto FIG. 8.

FIG. 8 illustrates a graph 180 showing various measurements takendirectly from and derived from eECAP signals generated by nerve fibersafter cessation of an applied burst of electrical stimulation inaccordance with various techniques consistent with this disclosure. In asame manner as illustrated in graph 170 of FIG. 7, graph 180 of FIG. 8illustrates trace 171 illustrating the peak amplitudes of the eECAPsignal associated with the Aα Type I nerve fibers following cessation ofthe 10 kHz burst, and trace 172 illustrating the peak amplitudes of theeECAP signal associated with the Aα Type II nerve fibers followingcessation of the same 10 kHz burst. Graph 180 also illustrates a trace173 representative of a least squares fit to the Aα Type I data of trace171. Graph 180 is further illustrative of examples of parametersassociated with the eECAP signals and traces that may be used toclassify the eECAP signals.

As illustrated in graph 180, a time period 182 can be measured thatindicates a time period between the cessation of the 10 kHz burst andthe time when the amplitude value of the eECAP signal for the Aα Type 1nerve fibers reaches a predetermined value. By way of example, a valueof 30 μV (circled in graph 180), is used as the predetermined amplitudevalue for determining this parameter. The time period 182 ofapproximately 9 seconds is measured as value (length) for the timeperiod between cessation of the 10 kHz burst and the time when the valueof the amplitude of the eECAP associated with the Aα Type I nerve fibersreaches a value of 30 μV, which corresponds to the predeterminedamplitude value. The length of time period 182 may be used as a baselinevalue for this parameter, and the corresponding parameter value asmeasured for one or more eECAP signals measured in response to theapplication of candidate therapies may be used to determine if the eECAPgenerated by the candidate therapy is different from or equivalent to,and/or is a match for the baseline eECAP. In various examples, thepredetermined value may be useful in that the value determines athreshold level where a patient may begin to feel a pain sensation basedon the level of nerve firing, and where another stimulation therapy mayneed to be applied to again drive down the amplitude of the level of thesignal being generated by the nerve fibers.

In another example of a eECAP signal parameters as shown in graph 180,an area 184 below trace 171 or trace 173 that is bounded by a firstpredetermined time (e.g., 10 seconds) and a second predetermined latertime (e.g., 20 seconds) following cessation of the 10 kHz burst may becalculated to determine a parameter associated with the eECAP signalcorresponding to trace 171 or 173. This calculated parameter may be usedto classify the eECAP signal against a baseline (e.g., is different fromor equivalent to baseline), or to determine if the eECAP signal sensedto generate trace 171 or 173 is a match for a predefined eECAP signal bycomparison of the value of area 184 to the corresponding area valuecalculated for the predefined eECAP signal. Thus, the value calculatedfor area 184 is another example of a parameter associated with an eECAPsignal that may be used to classified the eECAP responses.

In another example of an eECAP signal parameters that may be used toclassify eECAP signals, a difference value 186 may be determined for thedifference in amplitude values for the Aα Type I and the Aα Type IInerve fibers at one or more predetermined times after cessation of the10 kHz burst. As illustrated in graph 180, a difference value betweenthe amplitude of trace 172, representative of the amplitude value of theAα Type II nerve fibers, and the amplitude of trace 171, representativeof the amplitude value of the Aα Type I nerve fibers, may be measured atsome predetermined time, e.g., 5 seconds after cessation of the 10 kHzburst. The difference values 186 may be stored as a baseline value, andused to compare with the corresponding values measured for other eECAPsignals generated in response to application of a candidate therapy todetermine whether the eECAP generated by the candidate therapy isdifferent from, equivalent to, and/or is a match for the baseline eECAP,as described above with respect to other eECAP parameters. Measurementof difference value 186 is not limited to being taken at any particulartime period following cessation of the 10 kHz bust, and is not limitedto only include a signal difference value taken at one particular time.In some examples, multiple measurements of the difference value betweenthe signals may be taken at different times, respectively. In someexamples, each of these measured difference values may be used as anindividual eECAP parameter for comparing eECAP signals. In otherexamples, multiple measurements of the difference values for a given setof eECAP signals associated with a same stimulation therapy may becombined, for example added together and averaged, to form a singleoverall difference value for that eECAP. This overall difference valuemay then be used as an eECAP parameter for comparing a baseline eECAPsignal to one or more eECAP signals generated by the application ofcandidate therapies to a patient. These examples of eECAP parameters, asillustrated by graph 180, are intended to be non-limiting illustrativeexamples, and in no way limit the number and types of parameters thatare contemplated for use by the systems, devices, and methods of thepresent disclosure for use in comparing eECAP signals.

FIG. 9 is a flow diagram illustrating an example method 200 foradjusting electrical stimulation therapy parameters based on sensedeECAP signals in response to applied stimulation in accordance withvarious techniques consistent with this disclosure. Although discussedwith respect to IMD 14 of FIG. 1, the method 200 of FIG. 9 may beimplemented, in whole or in part, by system 22 of FIG. 2, and may beimplemented, in whole or in part, by system 120 of FIG. 5. In variousexamples, method 200 may be performed in whole or in part by any of theprocessing circuitry described herein. In various examples, it may bedesirable to influence the dynamics of the dorsal column in anequivalent manner that was achieved with a particular stimulationtherapy, for example using a 10 kHz stimulation burst, but using astimulation therapy with a different set of therapy parameters, forexamples a stimulation therapy provided at a lower frequency. Using thefrequency example for therapy parameters, this may be done by adaptingthe SCS frequency until the characterized eECAP no longer matches theinitial characterization achieved when using the higher frequencystimulation therapy. The approach is useful for defining the parameterlimits (e.g., the “metes and bounds”) over which alternative therapyparameters can be used to provide an equivalent therapy result relativeto a baseline result but using a different set of therapy parameters.The alternative therapy may provide an equivalent level of therapyefficacy, but provide one or more system performance advantages over theuse of the original therapy parameters.

As illustrated, in method 200 IMD 14 delivers electrical stimulation asa therapeutic or a diagnostic intervention (stimulation therapy) to apatient (block 202). IMD 14 senses an eECAP signal generated by one ormore nerve fiber bundles in response to the delivered electricalstimulation, and classifies the sensed eECAP signal as a baseline (block204). Classification of the sensed eECAP signal may comprise measurementand/or derivation of any type of parameter associated with the sensedeECAP signal. IMD 14, e.g., processing circuitry 80 of IMD 14,determines a change to a parameter that is used to generate a candidatetherapy, the candidate therapy different from the therapeutic/diagnosticintervention stimulation that resulted in the sensed eECAP baselinesignal (block 206). In some examples, the change in a parametercomprises lowering the frequency parameter of the electrical stimulationused in the candidate therapy relative to the frequency of theelectrical stimulation used in the therapeutic/diagnostic interventiontherapy. In some examples, lowering the frequency comprises lowering thefrequency by some predetermined and incremental amount. In someexamples, a change in parameters may be determined based at least inpart when there has been a detected change in activity level or postureof the patient. IMD 14 then delivers the candidate therapy based on thegenerated candidate therapy parameters (block 208). IMD 14 senses aneECAP signal generated by the one or more nerve fiber bundles inresponse to the delivered candidate therapy, and classifies the sensedeECAP signal (block 210). Classification of the sensed eECAP signal maycomprise measurement and/or derivation of any type of parameterassociated with the sensed eECAP signal, and comparison of theseparameters to the corresponding parameters associated with the eECAPbaseline.

IMD 14 determines if the sensed eECAP signal generated in response tothe candidate therapy is different over the baseline (block 212). If IMD14 determines that the sensed eECAP signal generated in response to thecandidate therapy is not different over the baseline eECAP signal, (a“NO” output is generated at block 212), the process of method 200 movesto block 214. At block 214, IMD 14 updates the therapy parameter thatwas initially changed at block 206. Updating the therapy parameter insome examples includes a further incremental adjustment of the value ofthe therapy parameter relative to the value used for that parameter inthe last applied candidate therapy. In some examples, an update inparameters may be determined based at least in part on when there hasbeen a detected change in activity level or posture of the patient. Thefurther updated therapy parameter is then provided to block 206, whereinIMD 14 uses the updated therapy parameter to generate a new candidatetherapy using the updated parameter. The candidate therapy generatedusing the updated parameter is delivered to the patient (block 208).

IMD 14 again senses the eECAP signal generated by the one or more nervefiber bundles in response to the delivered candidate therapy, and againclassifies the sensed eECAP signal (block 210). Again, IMD 14 determinesif the sensed eECAP signal generated in response to the candidatetherapy including the most recently updated parameter is different overthe baseline (block 212). If IMD 14 again determines that the sensedeECAP signal generated in response to the candidate therapy is notdifferent over the baseline eECAP signal, (a “NO” output is generated atblock 212), and the process of method 200 moves again back to block 214to again update the therapy parameter. In various examples of method200, the number of times the therapy parameter is updated and a newcandidate therapy is generated and delivered based on the updatedtherapy parameter is not limited to any particular number of iterations.In some examples, the process of updating therapy parameters, generatingand delivering candidate therapy based the update to the therapyparameter, sensing and classifying the eECAP signal that occurred inresponse to the candidate therapy, and determining if the eECAP signalis different from the baseline can be performed until a “YES” output isgenerated at block 212.

In various examples, a “YES” output is generated by IMD 14 when IMD 14determines that a sensed and categorized eECAP signal generated inresponse to any of the candidate therapies is different over (i.e., isnot equivalent to) the baseline. When the “YES” output decision isdetermined at block 212, method 200 proceeds to block 216, wherein IMD14 establishes a parameter boundary for the therapy parameter thatprovides an eECAP signal equivalent to the baseline. In variousexamples, the parameter boundary for the therapy parameter isestablished as the last therapy parameter that was used to generate acandidate therapy that was applied to the patient and resulted in asensed and categorized eECAP signal that was not different from thebaseline.

By using process of method 200, a therapy parameter associated with thedelivery of stimulation therapy can be changed, for exampleincrementally, and delivered as a candidate therapy. The sensed eECAPsignal the results from the delivery of the candidate therapy can becompared to one or more aspects and/or one or more parameters associatedwith a baseline eECAP signal, to determine if the candidate therapy canbe used to generate an equivalent eECAP signal response as generated bythe baseline therapy, and thus provide a same or substantiallyequivalent therapy treatment, but using different therapy parameter thatmay provide a performance or other advantage over the baseline therapy.Examples of such an advantage would be a longer battery life for IMD 14,or for example less exposure of the patient to higher frequency orstronger electrical fields associated with applied stimulation therapy.By using the iterative process described by method 200, a parameterboundary associated with a therapy parameter, such as a lower limit, canbe determined for the therapy parameter that, when incorporated into astimulation therapy and delivered to a patient, may provide a same levelof efficacy of treatment, but with one or more benefits and advantagesover operations with the therapy parameter not set at the therapyparameter boundary.

FIG. 10 is a flow diagram illustrating an example method 230 for testingelectrical stimulation therapy parameters based on a sensed eECAP inresponse to applied stimulation in accordance with various techniquesconsistent with this disclosure. Although discussed with respect to IMD14 of FIG. 1, the method 230 of FIG. 10 may be implemented, in whole orin part, by system 22 of FIG. 2, and may be implemented, in whole or inpart, by system 120 of FIG. 5. In various examples, method 230 may beperformed in whole or in part by any of the processing circuitrydescribed herein. In various examples, it may be desirable to test aproposed stimulation therapy that comprise one or more therapyparameters that are unlike any set of therapy parameters that have beenapplied as stimulation therapy to a patient, but that might provide somefeature or advantage, such as better patient comfort or safety, orbetter system performance, such as longer battery life, but that mayonly be useful if the proposed therapy parameters provide an equivalentlevel of treatment efficacy, or at least some minimum level of treatmentefficacy. The use of the eECAP according the method 230 provides amethod to evaluate these proposed treatments as follows.

As illustrated in method 230, IMD 14 delivers electrical stimulation asa therapeutic or a diagnostic intervention (stimulation therapy) to apatient (block 232). IMD 14 senses an eECAP signal generated by one ormore nerve fiber bundles in response to the delivered electricalstimulation, and classifies the sensed eECAP signal as a baseline signal(block 234). Method 200 further includes generation of a candidatetherapy (block 236). In some examples, the therapy parameters for thecandidate therapy may be provided as an input from a clinician or aphysician, such as by using programmer 20, to allow inputs regarding thedesired therapy parameters for the candidate therapy, and to communicatethese parameters to IMD 14 in any of the techniques described herein. Invarious examples, the parameters for the candidate therapy may beparameters that were previously stored n IMD 14. In various examples,the parameters for candidate therapy may include some parametersprovided to IMD 14, for example from programmer 20, and other parametersthat were previously stored in IMD 14. In various examples, one or moreof the therapy parameters for the candidate therapy may be automaticallygenerated by IMD 14. In some examples, generation of the candidatetherapy parameters may be determined based at least in part on adetected change in activity level or a detected posture of the patient.

Once the candidate therapy based on the candidate therapy parameters hasbeen defined and generated, IMD 14 delivers the candidate therapy to apatient (block 238). Following delivery of the candidate therapy, IMD 14senses an eECAP signal generated by the one or more nerve fiber bundlesin response to the delivered candidate therapy, and classifies thesensed eECAP signal (block 240). Classification of the sensed eECAPsignal may comprise measurement and/or derivation of any type ofparameter associated with the sensed eECAP signal, and comparison ofthese parameters to the corresponding parameters associated with theeECAP baseline.

Based on the sensed and classified eECAP signal, IMD 14 determines ifthe sensed and classified eECAP signal is different from the baseline(block 242). If IMD 14 determines that the sensed and classified eECAPsignal is not different from the baseline (a “NO” output from block242), then a determination has been made that the candidate therapy isequivalent to the baseline therapy (block 246). In the alternative, ifIMD 14 determines that the sensed and classified eECAP signal isdifferent from the baseline (a “YES” output from block 242), then adetermination has been made that the candidate therapy is not equivalentto the baseline therapy (block 246). By determining that the candidatetherapy is equivalent to the baseline, the candidate therapy may beprovided to a patient to achieve the same level of efficacy of treatmentthat is provided by the therapy treatment used to generate the baseline,but with the advantages provided by using the parameters of thecandidate therapy. On the other hand, if the candidate therapy isdetermined to not be equivalent to the baseline, then the candidatetherapy is also determined to not necessarily be capable of providing asame level of efficacy of treatment provided by the therapy treatmentused to generate the baseline.

In various examples, the difference between the eECAP signal generatedin response to the candidate therapy and the eECAP signal generated inresponse to the therapy treatment that generated the baseline may beused to evaluate tradeoffs between the two therapy treatments. Forexample, if the difference allows for a saving of some percentage ofbattery power using the candidate therapy, but the time betweenapplications of the candidate therapy is decreased (e.g., therapy needsto be applied more often), a conscious decision could be made to use thecandidate therapy in order to increase battery life at the expense ofmore frequent application of therapy. Many other types of comparisonsand trade-off analysis would be possible by comparison of the eECAPresponse generated by the candidate therapy to the baseline, and arecontemplated by use of method 230.

FIG. 11 is a flow diagram illustrating an example method 260 foradjusting electrical stimulation therapy parameters based on a sensedeECAP in response to applied stimulation in accordance with varioustechniques consistent with this disclosure. Although discussed withrespect to IMD 14 of FIG. 1, the method 260 of FIG. 11 may beimplemented, in whole or in part, by system 22 of FIG. 2, and may beimplemented, in whole or in part, by system 120 of FIG. 5. In variousexamples, method 260 may be performed in whole or in part by any of theprocessing circuitry described herein. In various examples, it isdesirable to adapt therapy to a particular set of eECAP parameters thatare known to provide a therapeutically optimal state. As an example, aneECAP initial area under the curve of 20 μV/millisecond with a τ (time)of 15 seconds may be optimal for a particular patient. The therapy pulseshape, amplitude, and/or frequency may be varied in one or morecombinations, and delivered as candidate therapies until a candidatetherapy that provides the particular set of eECAP parameters in an eECAPsignal generated in response to application of the candidate therapy tothe patient is achieved.

As shown for method 260, a set of target eECAP parameters is defined(block 262). In various examples the target eECAP parameters areparameters that are known to provide a particular therapeutically state,for example a therapeutic state that is optimal for a patient. A set ofcandidate therapy parameters is defined (block 264). In variousexamples, the candidate therapy parameters are a set of parameters thatinitially are not known to provide the therapy efficacy and orperformance levels for a system when provided by a therapy device, sucha s IMD 14, to a patient. In various examples, the candidate therapyparameters are determined based on one or more constraints fordelivering stimulation therapy to the patient, such as a maximum levelof a parameter that may be provided in association with a stimulationtherapy, or for example by a system constraint providing a limit to aparameter that can be provided by the system used to apply thestimulation therapy to the patient. For example, a maximum voltage levelthat a therapy system can deliver, or that may be safely delivered to apatient, may be a constraint on the candidate therapy parameters. Inanother example, a maximum frequency of the delivered stimulationtherapy than can be generated by the device generating and/or deliveringthe therapy, may be a constraint on the therapy parameters that arepossible for us in the candidate therapy. In some examples, defining thecandidate therapy parameters may be determined based at least in part ona detected change in activity level or a detected posture of thepatient.

Once the candidate therapy parameters are defined, IMD 14 generates thecandidate therapy based on the defined candidate therapy parameters(block 266). IMD 268 then delivers the candidate therapy (block 268).IMD 14 senses and classifies the eECAP signal generated in response tothe application of the candidate therapy to the patient (block 270).Classification of the sensed eECAP signal may comprise measurementand/or derivation of any type of parameter associated with the sensedeECAP signal, and comparison of these measurements to a baseline. IMD 14then determines if the sensed and classified eECAP signal matches thetarget eECAP parameters (block 272). A determination of whether thesensed and classified eECAP signal “matches” the target eECAP signal isnot limited to a determination based on any particular criteria, and maybe based on comparison of one or more parameters associated with thesensed and classified eECAP signal to the corresponding parametersassociated with the target eECAP signal. If IMD 14 determines that thesensed and categorized eECAP signal does not match the target eECAPparameters (a “NO” output from block 272), then a determination has beenmade that the candidate therapy is not equivalent to the baselinetherapy, and in some examples of method 260, the candidate therapyparameters are updated (block 274). Updating the candidate therapyparameters at block 274 may be performed automatically, for example byIMD 14, or may be performed by virtue of new inputs received for examplefrom programmer 20 to IMD 14, the inputs provided in some examples by aclinician or a physician. In some examples, updating of the candidatetherapy parameters may be determined based at least in part on adetected change in activity level or a detected posture of the patient.

The further updated therapy parameter is then provided to block 266,wherein IMD 14 uses the updated therapy parameter to generate a newcandidate therapy using the updated parameter. The candidate therapygenerated using the updated parameter is delivered to the patient (block268). IMD 14 again senses the eECAP signal generated by the one or morenerve fiber bundles in response to the delivered candidate therapy, andagain classifies the sensed eECAP signal (block 270). Again, IMD 14determines if the sensed eECAP signal generated in response to thecandidate therapy including the most recently updated parameter matchesthe target eECAP parameters (block 272). If IMD 14 again determines thatthe sensed eECAP signal generated in response to the candidate therapydoes not match the target eECAP parameters, a “NO” output is generated(at block 272), and the process of method 200 moves again back to block274 to update the therapy parameters. In various examples of method 260,the number of times the therapy parameter is updated and a new candidatetherapy is generated and delivered based on the updated therapyparameter is not limited to any particular number of iterations. In someexamples, the process of updating therapy parameters, generating anddelivering candidate therapy based the updates to the therapy parameter,sensing and classifying the eECAP signal that occurred in response tothe candidate therapy, and determining if the eECAP signal matches thetarget eECAP parameters can be performed until a “YES” output isgenerated at block 272.

If at block 272 IMD 14 determines that that the sensed and categorizedeECAP signal does match the target eECAP parameters (a “YES” output fromblock 272), then a determination is made the target eECAP signalresponse has been achieved by the application of the candidate therapyto the patient. This determination may indicate that the candidatetherapy may be provided to the patient to produce the targeted eECAPresponse, and thus the desired therapy efficacy and/or a desired set ofperformance parameters for the system delivering the stimulation to thepatient.

FIG. 12 is a flow diagram illustrating an example method 300 foradjusting electrical stimulation therapy parameters based on a sensedeECAP in response to applied stimulation in accordance with varioustechniques consistent with this disclosure. Although discussed withrespect to IMD 14 of FIG. 1, the method 300 of FIG. 12 may beimplemented, in whole or in part, by system 22 of FIG. 2, and may beimplemented, in whole or in part, by system 120 of FIG. 5. In variousexamples, method 300 may be performed in whole or in part by any of theprocessing circuitry described herein. In various examples,characteristics of the eECAP may be used to trigger delivery of apre-defined neurostimulation therapy. For instance, a particularelectrical stimulation therapy can be delivered to the dorsal column orthe neural target. Following cessation of the therapy, eECAP can be usedas a tool to monitor the dynamics of the neural target previouslystimulated until a particular eECAP is seen. The occurrence of thisparticular eECAP can be used as a trigger to deliver more therapy. Inother examples, the occurrence of this particular eECAP can be used as atrigger to cease deliver of further therapy.

As illustrated in method 300, IMD 14 delivers electrical stimulationtherapy to a patient (block 302). At some point in time, IMD ceasesdelivery of the stimulation therapy (block 304). IMD 14 then senses aneECAP signal generated by one or more nerve fiber bundles in response tothe delivered electrical stimulation, and classifies the sensed eECAPsignal. Classification of the sensed eECAP signal is not limited to anyparticular means of classification, and in some examples comprisesdetermining one or more parameters directly measured from and/or derivedfrom the parameters of sensed eECAP signal. Classification of the eECAPsignal in various examples includes determining whether the parametersassociated with the sensed eECAP signal include values that fall with agiven range of values for the parameter, or in some examples if thevalue of one or more parameters associated with the sensed eECAP signalexceeds a predetermined threshold value, or does not exceed apredetermined threshold value.

At block 308, IMD 14 determines if a particular eECAP is sensed (block308). In some examples, determining if a particular eECAP is sensedcomprises comparing a value for one or more of the parameters associatedwith the sensed eECAP signal to a template and/or to one or morepredetermined values for the one or more parameters. If a determinationis made that the sensed eECAP is not the particular eECAP (a “NO” isgenerated at block 308), then method returns to block 306, and againsenses and classifies the eECAP signal at this later time. In thealternative, if a determination is made at block 308 that the particulareECAP is sensed (a “YES” is generated at block 308), and method 300proceeds to block 310.

At block 310, IMD 14 determines if more therapy is to be delivered. Insome examples, determining if more therapy is to be delivered is basedon a predetermined rule programmed or otherwise stored in IMD 14 thatdictates whether more therapy is to be delivered when the particulareECAP is sensed. In some examples, a determination of whether moretherapy is to be delivered may be based at least in part on a detectedchange in activity level or a detected posture of the patient. If adetermination is made at block 310 that no more therapy is to bedelivered, (a “NO” is generated at block 310), then method proceeds toblock 312, were IMD 14 ceases further delivery of stimulation therapy.In the alternative, if a determination is made at block 310 that moretherapy is to be delivered, (a “YES” is generated at block 310), andmethod 300 proceed to block 314.

At block 314, IMD 14 determines whether to adjust therapy parameters. Insome examples, determining whether to adjust therapy parameters is basedon a predetermined rule programmed or otherwise stored in IMD 14. Forexample, IMD 14 may be running a pre-programmed set of stimulationtherapies as part of method 300 that sets up incremental changes for oneor more of the therapy parameters used to deliver therapy at block 302.In some examples, a determination of whether to adjust the therapyparameters may be based at least in part on a detected change inactivity level or a detected posture of the patient.

As such, IMD 14 at block 314 may determine that an adjustment of one ormore of the therapy parameters is required, and generates a “YES” outputat block 314. If IMD 14 generates a “YES” output at block 314, method315 proceeds to block 316. At block 316, IMD 14 adjusts one or moretherapy parameters, and generates a new therapy based on the updatedtherapy parameters. Once the new therapy has been generated, method 300proceeds to block 302, wherein at block 302 IMD 14 delivers stimulationtherapy based on the new therapy and the adjusted therapy parameters,and IMD 14 continues to execute the processes of method 300 as describedabove. The number of iteration of adjusting therapy parameters anddelivering stimulation therapy based on the new therapy is not limitedto any particular number iterations, and in some examples continuesuntil IMD 14 determines that no more therapy is to be delivered at block310.

In the alternative, if at block 314 IMD 14 determination that noadjustments to the therapy parameters are to be made, (a “NO” output isgenerated at block 314), and method 300 proceeds to block 302, whereinIMD 14 delivers stimulation therapy based on the therapy parameters usedin conjunction with the more recently applied stimulation therapy. Afterdelivering stimulation therapy at block 302, IMD 14 continues to executethe processes of method 300 as described above.

FIG. 13 a flow diagram illustrating an example method 330 for adjustingelectrical stimulation therapy parameters based on a sensed eECAP inresponse to applied stimulation in accordance with various techniquesconsistent with this disclosure. Although discussed with respect to IMD14 of FIG. 1, the method 330 of FIG. 13 may be implemented, in whole orin part, by system 22 of FIG. 2, and may be implemented, in whole or inpart, by system 120 of FIG. 5. In various examples, method 330 may beperformed in whole or in part by any of the processing circuitrydescribed herein. In various examples, time may also be used as part ofa feedback loop. For instance, a neurostimulation therapy may bedelivered to the neural target. The system may decide to deliver or notdeliver further neurostimulation therapy based on a determination as towhether a specific eECAP is or isn't seen within a fixed period of timerelative to the delivery of the neurostimulation therapy.

As illustrated, in method 330 IMD 14 delivers electrical stimulationtherapy to a patient (block 332). At some point in time, IMD ceasesdelivery of the stimulation therapy (block 334). IMD 14 then senses aneECAP signal generated by one or more nerve fiber bundles in response tothe delivered electrical stimulation, and classifies the sensed eECAPsignal (block 336). Classification of the sensed eECAP signal is notlimited to any particular means of classification, and in some examplescomprises determining one or more parameters directly measured fromand/or derived from the parameters of sensed eECAP signal.Classification of the eECAP signal in various examples includesdetermining whether the parameters associated with the sensed eECAPsignal include values that fall with a given range of values for theparameter, or in some examples if the value of one or more parametersassociated with the sensed eECAP signal exceed or do not exceed apredetermined threshold value set for the corresponding parameter.

Following sensing and classification of the eECAP signal, IMD 14determines if a particular eECAP is sensed (block 338). In someexamples, determining if a particular eECAP is sensed comprisescomparing a value for one or more of the parameters associated with thesensed eECAP signal to a template and/or to one or more baseline valuesfor the one or more parameters. If a determination is made that thesensed eECAP is not the particular eECAP (a “NO” is generated at block338), then method 330 proceeds to block 340, and wherein IMD 14determines if a predetermined time limit for either sensing or for notsensing the particular eECAP signal has expired. If the predeterminedtime limit has not expired (a “NO” is generated at block 340), method330 returns to block 336, wherein IMD 14 again senses and classifies theeECAP signal. In the alternative, if the predetermine time limit hasexpired (a “YES” is generated at block 340), method 330 proceeds toblock 342, where IMD 14 determines if more therapy is to be delivered.In some examples, a determination of whether more therapy is to bedelivered may be based at least in part on a detected change in activitylevel or a detected posture of the patient. If IMD 14 determines that nomore therapy is to be delivered (a “NO” is generated at block 342),method 330 proceed to block 344, wherein IMD 14 ceased to furtherdelivery of stimulation therapy. If in the alternative IMD 14 determinesat block 342 that more therapy is to be delivered (a “YES” is generatedat block 342), method 330 proceed to block 346.

At block 346, IMD 14 may adjust any parameters to the therapy parametersthat will be utilized during next stimulation therapy to be applied tothe patient, generates the next stimulation therapy, and method 330 thenreturns to block 332, where IMD 14 delivers the new stimulation therapy.In some examples, the new stimulation therapy is delivered using thesame set of therapy parameters used in the generation and delivery ofthe previously delivered stimulation therapy. In some examples, the newstimulation therapy is delivered using one or more therapy parametersthat are different in value from the therapy parameters used in thepreviously delivered stimulation therapy. In some examples, adetermination of whether to adjust any therapy parameters may be basedat least in part on a detected change in activity level or a detectedposture of the patient.

Referring back to block 338, if after sensing and classifying the eECAPsignal IMD 14 determines that the particular eECAP signal was sensed,method 330 proceeds to block 342, where a determination as to whethermore therapy is to be delivered is made, as described above. Once atblock 342, method 330 proceeds as described above, wherein IMD 14 mayeither cease further delivery of stimulation therapy, or may adjust oneor more parameters and generate a new stimulation therapy for deliveryto the patient. Determinations as to whether more therapy is to bedelivered based on sensing or not sensing a particular eECAP signal arenot limited to any particular decision criteria, and may be based onrules defined by a clinician and/or a physician and stored in IMD 14 foruse in the decisions made as part of the processes performed by method330.

The techniques of this disclosure may be implemented in a wide varietyof computing devices, medical devices, or any combination thereof. Anyof the described units, modules or components may be implementedtogether or separately as discrete but interoperable logic devices.Depiction of different features as modules or units is intended tohighlight different functional aspects and does not necessarily implythat such modules or units must be realized by separate hardware orsoftware components. Rather, functionality associated with one or moremodules or units may be performed by separate hardware or softwarecomponents, or integrated within common or separate hardware or softwarecomponents.

The techniques described in this disclosure may be implemented, at leastin part, in hardware, software, firmware or any combination thereof. Forexample, various aspects of the techniques may be implemented within oneor more microprocessors, digital signal processors (DSPs), applicationspecific integrated circuits (ASICs), field programmable gate arrays(FPGAs), or any other equivalent integrated or discrete logic circuitry,as well as any combinations of such components, embodied in programmers,such as physician or patient programmers, stimulators, or other devices.The terms “processor,” “processing circuitry,” “controller” or “controlmodule” may generally refer to any of the foregoing logic circuitry,alone or in combination with other logic circuitry, or any otherequivalent circuitry, and alone or in combination with other digital oranalog circuitry.

For aspects implemented in software, at least some of the functionalityascribed to the systems and devices described in this disclosure may beembodied as instructions on a computer-readable storage medium such asrandom access memory (RAM), read-only memory (ROM), non-volatile randomaccess memory (NVRAM), electrically erasable programmable read-onlymemory (EEPROM), FLASH memory, magnetic media, optical media, or thelike that is tangible. The computer-readable storage media may bereferred to as non-transitory. A server, client computing device, or anyother computing device may also contain a more portable removable memorytype to enable easy data transfer or offline data analysis. Theinstructions may be executed to support one or more aspects of thefunctionality described in this disclosure.

In some examples, a computer-readable storage medium comprisesnon-transitory medium. The term “non-transitory” may indicate that thestorage medium is not embodied in a carrier wave or a propagated signal.In certain examples, a non-transitory storage medium may store data thatcan, over time, change (e.g., in RAM or cache).

Various examples of the devices, systems, and methods in accordance withthe description provided in this disclosure are provided below.

Example 1

A method comprising: delivering, by a stimulation electrode, electricalstimulation as a candidate therapy to a patient according to a set ofcandidate therapy parameters, the stimulation electrode located inproximity to the dorsal column of a patient; sensing, by a sensingelectrode, an electrically evoked compound action potential (eECAP)signal in response to the delivery of the electrical stimulation;classifying, by a processor, the sensed eECAP signal generated inresponse to the application of the candidate therapy relative to aneECAP baseline; and determining, by the processor, if the sensed eECAPsignal is different over the eECAP baseline based on at least oneparameter used in classifying the sensed eECAP signal.

Example 2

The method of example 1, wherein classifying the sensed eECAP signalcomprises classifying the sensed eECAP signal based on the at least oneparameter directly measured from or derived from the at least oneparameter of the sensed eECAP signal.

Example 3

The method of example 2, wherein classifying the sensed eECAP signalbased on the at least one parameter comprises comparing a value for theparameter to a value or a range of values for a corresponding parametermeasured or derived from a baseline eECAP signal used to generate theeECAP baseline.

Example 4

The method of any one of examples 2-3, wherein the parameter measured orderived from the sensed eECAP signal comprises a measure of fiberlatency in the sensed eECAP signal.

Example 5

The method of any of examples 2-4, wherein the parameter measured orderived from the sensed eECAP signal comprises a measure of a time whenmasking occurs for a portion of the sensed eECAP signal attributed to aspecific nerve fiber type.

Example 6

The method of any of examples 2-5, wherein the parameter measured orderived from the sensed eECAP signal comprises a measurement of thewidth of the eECAP signal.

Example 7

The method of any of examples 2-6, wherein the parameter measured orderived from the eECAP signal comprises an amplitude of the eECAPsignal.

Example 8

The method of any of examples 2-7, wherein the parameter measured orderived from the eECAP signal comprises an area under a portion of acurve of the amplitude of the eECAP signal.

Example 9

The method of any of examples 2-8, wherein the parameter measured orderived from the eECAP signal comprises a ratio of eECAP amplitude forthe eECAP signal attributed to a first nerve fiber type versus the eECAPamplitude for the eECAP signal attributed to a second nerve fiber typediffer from the first nerve fiber type.

Example 10

The method of any of examples 2-9, wherein parameter measured or derivedfrom the eECAP signal comprises a difference value between the fiberlatency for a first nerve fiber type with respect the fiber latency fora second nerve fiber type that is a different nerve fiber type than thefirst nerve fiber type.

Example 11

The method of any of examples 2-10, wherein classifying the sensed eECAPsignal based on the parameter measured or derived from the sensed eECAPsignal comprises determining if a value of the parameter from the sensedeECAP signal does not exceed a threshold value determined for thecorresponding parameter value of the eECAP baseline.

Example 12

The method of any of examples 2-11, wherein classifying the sensed eECAPsignal based on the parameter measured or derived from the sensed eECAPsignal comprises determining if a value of the parameter from the sensedeECAP falls within a predetermined range of values determined by acorresponding parameter value of the eECAP baseline.

Example 13

The method of any of examples 1-12, further comprising:

determining, by the processor, whether to adjust one or more of thetherapy parameters used to deliver stimulation therapy to a patientbased on the classification of the sensed eECAP signal.

Example 14

The method of any of examples 1-13, where classifying the sensed eECAPsignal relative to the eECAP baseline comprises determining whether thesensed eECAP signal is equivalent to the eECAP baseline.

Example 15

The method of any of examples 1-14, wherein the eECAP baseline isestablished by applying a baseline stimulation therapy having a set ofbaseline set of therapy parameters to a patient, and sensing an eECAPsignal generated as a result of the application of the baselinestimulation therapy.

Example 16

The method of any of examples 1-15, further comprising: detecting achange in patient posture from a first posture state to a second posturestate; and in response to detection of the change in patient posture,detecting a second signal including the eECAP in response to theapplication of the stimulation therapy.

Example 17

The method of example 16, further comprising: responsive to detectingthe change in patient posture, applying the stimulation therapyaccording to a second set of stimulation therapy parameters associatedwith the second posture state; detecting the second signal including theeECAP in response to the application of stimulation therapy according tothe second set of stimulation therapy parameters; and adjusting one ormore of the stimulation parameters of the second set of stimulationparameters based on the detected signal.

Example 18

The method of any of examples 1-17, wherein the eECAP baseline is astored eECAP signal.

Example 19

The method of any of examples 1-18, further comprising detecting thesignal including the eECAP in response to the application of thestimulation therapy at a predetermined time interval following cessationof the application of the stimulation therapy.

Example 20

The method of any of claims 1-19, wherein electrical stimulation as acandidate therapy comprises at least one therapy parameter having avalue that is different from the value of the corresponding therapyparameter applied as electrical stimulation to the patient in order togenerate the eECAP baseline.

Example 21

The method of example 20, wherein the at least one therapy parameter ofthe of the candidate therapy that is different from the value of thecorresponding therapy parameter applied as electrical stimulation to thepatient in order to generate the eECAP baseline, comprises candidatetherapy having a higher frequency.

Example 22

The method of example 21, wherein the higher frequency comprises afrequency in a range of 10-15 kHz.

Example 23

The method of any of examples 1-22, wherein determining, by theprocessor, if the sensed eECAP signal is different over the eECAPbaseline based on at least one parameter used in classifying the sensedeECAP signal further comprises: determining, by the processor, that thesensed eECAP signal is different over the eECAP baseline; andestablishing, by the processor, a parameter boundary for at least one ofthe therapy parameters used to generate a candidate therapy that wasapplied to the patient and resulted in a sensed and categorized eECAPsignal that was not different from the baseline.

Example 24

The method of any of examples 1-23, wherein determining, by theprocessor, if the sensed eECAP signal is different over the eECAPbaseline based on at least one parameter used in classifying the sensedeECAP signal further comprises: determining, by the processor, that thesensed eECAP signal is not different over the eECAP baseline; updating,by the processor at least one therapy parameter of the candidate therapyand generating a new candidate therapy based on the updated therapyparameter; delivering, by a stimulation electrode, electricalstimulation as a new candidate therapy to a patient according the newcandidate therapy parameters, sensing, by a sensing electrode, anelectrically evoked compound action potential (eECAP) signal in responseto the delivery of the electrical stimulation; classifying, by aprocessor, the sensed eECAP signal generated in response to theapplication of the new candidate therapy relative to an eECAP baseline;and determining, by the processor, if the sensed eECAP signal isdifferent over the eECAP baseline based on at least one parameter usedin classifying the sensed eECAP signal.

Example 25

A system comprising: one or more electrodes; a stimulation generatorconfigured to apply stimulation therapy via the one or more electrodesbased on a set of stimulation therapy parameters; and a processorconfigured to: generate the candidate therapy parameters, control thestimulation generator to provide the candidate stimulation therapy tothe one or more electrodes based on the candidate therapy parameters,sense an electrically evoked compound action potential (eECAP) signalgenerated in response to the application of the candidate stimulationtherapy, classify the sensed eECAP signal based on an eECAP baseline;and determine if the sensed eECAP signal is different over the eECAPbaseline based on at least one parameter used in classifying the sensedeECAP signal.

Example 26

The system of example 25, further comprising a memory configured tostore stimulation parameters, wherein the processor is configured togenerate a third set of stimulation parameters including the one or morestimulation parameters in association with a change in posture state ofthe patient, and store the third set of stimulation parameters in thememory.

Example 27

The system of any of examples 25-26, wherein the processor is furtherconfigured to: compare one or more parameters of the sensed eECAP to oneor more corresponding parameters of the eECAP baseline; and adjust atleast one of the stimulation parameters based on the comparison; whereinthe one or more electrodes are further configured to provide stimulationtherapy based on an adjusted set of stimulation therapy parameters.

Example 28

The system of any of examples 25-27, wherein the processor is furtherconfigured to detect a signal including an eECAP in response to theapplication of the stimulation therapy at a predetermined interval fromthe application of the stimulation therapy.

Example 29

The system of any of examples 25-28, further comprising a memoryconfigure to store the set of stimulation parameters including at leastone adjusted stimulation parameter.

Example 30

The system of any of examples 25-29, wherein the one or more electrodesare further configured to detect a signal including the eECAP byelectrodes located at a distance from the targeted stimulation nervesite.

Example 31

The system of any of examples 25-30, wherein the one or more electrodesare further configured to apply the stimulation therapy to a dorsalcolumn of a patient.

Example 32

A system comprising: one or more electrodes; a stimulation generatorconfigured to apply stimulation therapy via the one or more electrodesbased on a set of stimulation therapy parameters; and a processorconfigured to: receive a detected signal including an evoked compoundaction potential (eECAP) in response to the application of thestimulation therapy; analyze the detected signal; and adjust at leastone of the stimulation parameters based on the analysis of the detectedsignal.

Example 33

The system of example 32, further comprising: a posture state moduleconfigured to detect a posture state of a patient; and wherein theprocessor is further configured to detect a change in the posture statefrom a first posture state to a second posture state, and in response todetection of the change in patient posture from the first posture stateto the second posture state, detect the signal including an eECAP inresponse to the application of the stimulation therapy.

Example 34

The system of example 33, further comprising: wherein the set ofstimulation parameter comprises a first set of stimulation parameters;wherein the stimulation generator is further configured to providestimulation according to a second set of stimulation therapy parametersassociated with the second posture state; and wherein the processor isfurther configured to: detect the signal including an eECAP in responseto the application of stimulation therapy according to the second set ofstimulation therapy parameters; and adjust at least one of thestimulation parameters of the second set of stimulation parameters basedon the eECAP detected in response to application of the second set ofstimulation therapy parameters.

Example 35

A system comprising: means for applying stimulation therapy to a patientaccording to a set of stimulation therapy parameters; means for sensinga signal including an electrically evoked compound action potential(eECAP) in response to the application of the stimulation therapy; andmeans for classifying the sensed eECAP signal at least in part based ona baseline eECAP.

Example 36

The system of example 35, wherein the means for classifying the sensedeECAP signal comprises means for classifying the sensed eECAP signalbased on a parameter measured or derived from the sensed eECAP signal.

Example 37

The system of any of examples 35-36, further comprising means forperforming any of the methods descried herein.

Example 38

A non-transitory computer readable medium comprising instructions forcausing a programmable processor to perform any of the methods describedin examples 1-24.

Example 39

A non-transitory computer readable medium comprising instructions forcausing a programmable processor to perform any of the methods describedherein.

Example 40

A method comprising: delivering, by a stimulation electrode, electricalstimulation as a baseline therapy to a patient according to a set ofbaseline therapy parameters, the stimulation electrode located inproximity to the dorsal column of the patient; sensing, by a sensingelectrode, an electrically evoked compound action potential (eECAP)signal in response to the delivery of the electrical stimulation as aneECAP baseline; determining, by a processor, a change to a therapyparameter to generate a candidate therapy having a set of candidatetherapy parameters; delivering, by the stimulation electrode, electricalstimulation based on the candidate therapy to the patient according tothe candidate therapy parameters; sensing, by the sensing electrode, anelectrically evoked compound action potential (eECAP) signal in responseto the delivery of the electrical stimulation based on the candidatetherapy; classifying, by the processor, the sensed eECAP signalgenerated in response to the application of the candidate therapyrelative to an eECAP baseline; determining, by the processor, if thesensed eECAP signal is different over the eECAP baseline based on atleast one parameter used in classifying the sensed eECAP signal; andestablishing, by the processor, a parameter boundary for the at leastone parameter as equivalent to the baseline if the sensed eECAP signalis determined to be different over the eECAP baseline.

Example 41

A method comprising: delivering, by a stimulation electrode, electricalstimulation as a baseline therapy to a patient according to a set ofbaseline therapy parameters, the stimulation electrode located inproximity to the dorsal column of the patient; sensing, by a sensingelectrode, an electrically evoked compound action potential (eECAP)signal in response to the delivery of the electrical stimulation as aneECAP baseline; generating, by a processor, a candidate therapy having aset of candidate therapy parameters; delivering, by the stimulationelectrode, electrical stimulation as a candidate therapy to the patientaccord to the set of candidate therapy parameters; sensing, by thesensing electrode, an electrically evoked compound action potential(eECAP) signal in response to the delivery of the electrical stimulationbased on the candidate therapy; classifying, by the processor, thesensed eECAP signal generated in response to the application of thecandidate therapy relative to an eECAP baseline; and determining, by theprocessor, if the sensed eECAP signal is different over the eECAPbaseline based on at least one parameter used in classifying the sensedeECAP signal, wherein determining if the sensed eECAP signal isdifferent over the eECAP baseline comprises deterring that the candidatetherapy is equivalent to the baseline therapy if the sensed eECAP signalis not different over the eECAP baseline, or that the candidate therapyis not equivalent to the baseline therapy if the sensed eECAP signal isdifferent over the eECAP baseline.

Example 42

A method comprising: defining, by a processor, one or more targetparameters for an electrically evoked compound action potential (eECAP)signal as a target eECAP; defining, by the processor, one or morecandidate therapy parameters; generating, by the processor, a candidatetherapy based on as set of the defined candidate therapy parameters;delivering, by a stimulation electrode, electrical stimulation based onthe generated candidate therapy to a patient according to the set ofcandidate therapy parameters, the stimulation electrode located inproximity to the dorsal column of the patient; sensing, by a sensingelectrode, an electrically evoked compound action potential (eECAP)signal in response to the delivery of the candidate therapy;classifying, by the processor, the sensed eECAP signal generated inresponse to the application of the candidate therapy relative to thetarget eECAP; and determining, by the processor, if the sensed eECAPsignal matches the target eECAP based on at least one parameter used inclassifying the sensed eECAP signal, wherein determining if the sensedeECAP signal matches the target eECAP comprises deterring that the atleast one parameter used in classifying the sensed eECAP signal matchesthe corresponding parameter or parameters of the target eECAP.

Example 43

A method comprising: delivering, by a stimulation electrode, electricalstimulation as a baseline therapy to a patient according to a set ofbaseline therapy parameters, the stimulation electrode located inproximity to the dorsal column of the patient; ceasing delivery of theelectrical stimulation by the stimulation electrode; sensing, by asensing electrode, an electrically evoked compound action potential(eECAP) signal in response to the delivery of the electrical stimulationas an eECAP signal; classifying, by a processor, the sensed eECAP signalgenerated in response to the application of the baseline therapyrelative to an eECAP baseline; determining, by the processor, if thesensed eECAP is a particular eECAP, the determination of whether thesensed eECAP is a particular eECAP based on one or more parameters usedto classify the sensed eECAP signal; and determining, by the processor,if more therapy is to be delivered to the patient based on thedetermination of whether the sensed eECAP was or was not the particulareECAP.

Example 44

A method comprising: delivering, by a stimulation electrode, electricalstimulation as a baseline therapy to a patient according to a set ofbaseline therapy parameters, the stimulation electrode located inproximity to the dorsal column of the patient; ceasing delivery of theelectrical stimulation by the stimulation electrode; sensing, by asensing electrode, an electrically evoked compound action potential(eECAP) signal in response to the delivery of the electrical stimulationas an eECAP signal; classifying, by a processor, the sensed eECAP signalgenerated in response to the application of the baseline therapy;determining, by the processor, if the sensed eECAP is a particulareECAP, the determination of whether the sensed eECAP is a particulareECAP based on one or more parameters used to classify the sensed eECAPsignal; determining, by the processor, if a time period has expiredfollowing ceasing delivery of the electrical stimulation; anddetermining, by the processor, if more therapy is to be delivered to thepatient based on the determination of whether the sensed eECAP was orwas not the particular eECAP and whether the time period has expired.

Various examples consistent with this disclosure have been described.These and other examples are within the scope of the following claims.

What is claimed is:
 1. A method comprising: delivering an initialelectrical stimulation therapy defined by a set of initial therapyparameters to a patient; sensing, in response to the delivery of theinitial electrical stimulation therapy, an initial electrically evokedcompound action potential (eECAP) signal; delivering a plurality ofdifferent candidate electrical stimulation therapies to the patient,each candidate electrical stimulation therapy of the plurality ofdifferent candidate electrical stimulation therapies defined by arespective set of candidate therapy parameters different from the set ofinitial therapy parameters; for each candidate electrical stimulationtherapy of the plurality of different candidate electrical stimulationtherapies, sensing, in response to delivery of the candidate electricalstimulation therapy, a respective eECAP signal; comparing, by processingcircuitry, the respective eECAP signal for each candidate electricalstimulation therapy of the plurality of different candidate electricalstimulation therapies to the initial eECAP signal; and selecting, by theprocessing circuitry and based on the comparison of the respective eECAPsignal for each candidate electrical stimulation therapy of theplurality of different candidate electrical stimulation therapies to theinitial eECAP signal, one of the plurality of different candidateelectrical stimulation therapies for subsequent electrical stimulation.2. The method of claim 1, wherein the set of initial therapy parameterscomprise a frequency selected from a range greater than or equal to10,000 Hertz, and wherein the set of candidate therapy parameters ofeach candidate electrical stimulation therapy of the plurality ofdifferent candidate electrical stimulation therapies comprises adifferent frequency selected from a range less than or equal to 1,200Hertz.
 3. The method of claim 1, wherein the set of initial therapyparameters comprise a frequency selected from a range greater than orequal to 10,000 Hertz and less than or equal to 15,000 Hertz, andwherein the set of candidate therapy parameters of each candidateelectrical stimulation therapy of the plurality of different candidateelectrical stimulation therapies comprises a different frequencyselected from a range greater than or equal to 0.5 Hertz and less thanor equal to 1,200 Hertz.
 4. The method of claim 1, wherein eachcandidate electrical stimulation therapy of the plurality of differentcandidate electrical stimulation therapies has a lower power consumptionthan the initial electrical stimulation therapy.
 5. The method of claim1, wherein comparing the respective eECAP signal for each candidateelectrical stimulation therapy of the plurality of different candidateelectrical stimulation therapies to the initial eECAP signal comprisesdetermining that a first eECAP signal of a first candidate electricalstimulation therapy of the plurality of different candidate electricalstimulation therapies matches the initial eECAP signal; and whereinselecting, based on the comparison of the respective eECAP signal foreach candidate electrical stimulation therapy of the plurality ofdifferent candidate electrical stimulation therapies to the initialeECAP signal, the one of the plurality of different candidate electricalstimulation therapies for subsequent electrical stimulation comprisesselecting, based on the determination that the first eECAP signal of thefirst candidate electrical stimulation therapy of the plurality ofdifferent candidate electrical stimulation therapies matches the initialeECAP signal, the first candidate electrical stimulation therapy forsubsequent electrical stimulation.
 6. The method of claim 5, whereindetermining that the first eECAP signal of the first candidateelectrical stimulation therapy of the plurality of different candidateelectrical stimulation therapies matches the initial eECAP signalcomprises determining that a value of at least one parameter of thefirst eECAP signal is within a range based on a value of at least oneparameter of the initial eECAP signal.
 7. The method of claim 5, whereindetermining that the first eECAP signal of the first candidateelectrical stimulation therapy of the plurality of different candidateelectrical stimulation therapies matches the initial eECAP signalcomprises determining that a value of at least one parameter of thefirst eECAP signal is less than a threshold value of at least oneparameter of the initial eECAP signal.
 8. The method of claim 5, whereincomparing the respective eECAP signal for each candidate electricalstimulation therapy of the plurality of different candidate electricalstimulation therapies to the initial eECAP signal further comprisesdetermining that a second eECAP signal of a second candidate electricalstimulation therapy of the plurality of different candidate electricalstimulation therapies is different from the initial eECAP signal.
 9. Themethod of claim 1, wherein comparing the respective eECAP signal foreach candidate electrical stimulation therapy of the plurality ofdifferent candidate electrical stimulation therapies to the initialeECAP signal comprises comparing at least one parameter of therespective eECAP signal for each candidate electrical stimulationtherapy of the plurality of different candidate electrical stimulationtherapies to at least one parameter of the initial eECAP signal.
 10. Themethod of claim 9, wherein the at least one parameter of the respectiveeECAP signal for each candidate electrical stimulation therapy of theplurality of different candidate electrical stimulation therapiescomprises one or more of: a fiber latency of the respective eECAPsignal; a time to specific fiber type masking of the respective eECAPsignal; a width of the respective eECAP signal; an offset of anamplitude, an area underneath a curve, a power or an integral of therespective eECAP signal; an initial value of an amplitude, an areaunderneath a curve, a power or an integral of the respective eECAPsignal; or a recovery time constant of the respective eECAP signal. 11.A system comprising: a stimulation generator configured to deliverelectrical stimulation therapy to a patient; and processing circuitryconfigured to: control the stimulation generator to deliver an initialelectrical stimulation therapy defined by a set of initial therapyparameters to the patient; sense, in response to the delivery of theinitial electrical stimulation therapy, an initial electrically evokedcompound action potential (eECAP) signal; control the stimulationgenerator to deliver a plurality of different candidate electricalstimulation therapies to the patient, each candidate electricalstimulation therapy of the plurality of different candidate electricalstimulation therapies defined by a respective set of candidate therapyparameters different from the set of initial therapy parameters; foreach candidate electrical stimulation therapy of the plurality ofdifferent candidate electrical stimulation therapies, sense, in responseto delivery of the candidate electrical stimulation therapy, arespective eECAP signal; compare the respective eECAP signal for eachcandidate electrical stimulation therapy of the plurality of differentcandidate electrical stimulation therapies to the initial eECAP signal;and select, based on the comparison of the respective eECAP signal foreach candidate electrical stimulation therapy of the plurality ofdifferent candidate electrical stimulation therapies to the initialeECAP signal, one of the plurality of different candidate electricalstimulation therapies for subsequent electrical stimulation.
 12. Thesystem of claim 11, wherein the set of initial therapy parameterscomprise a frequency selected from a range greater than or equal to10,000 Hertz, and wherein the set of candidate therapy parameters ofeach candidate electrical stimulation therapy of the plurality ofdifferent candidate electrical stimulation therapies comprises adifferent frequency selected from a range less than or equal to 1,200Hertz.
 13. The system of claim 11, wherein the set of initial therapyparameters comprise a frequency selected from a range greater than orequal to 10,000 Hertz and less than or equal to 15,000 Hertz, andwherein the set of candidate therapy parameters of each candidateelectrical stimulation therapy of the plurality of different candidateelectrical stimulation therapies comprises a different frequencyselected from a range greater than or equal to 0.5 Hertz and less thanor equal to 1,200 Hertz.
 14. The system of claim 11, wherein eachcandidate electrical stimulation therapy of the plurality of differentcandidate electrical stimulation therapies has a lower power consumptionthan the initial electrical stimulation therapy.
 15. The system of claim11, wherein to compare the respective eECAP signal for each candidateelectrical stimulation therapy of the plurality of different candidateelectrical stimulation therapies to the initial eECAP signal, theprocessing circuitry is configured to determine that a first eECAPsignal of a first candidate electrical stimulation therapy of theplurality of different candidate electrical stimulation therapiesmatches the initial eECAP signal; and wherein to select, based on thecomparison of the respective eECAP signal for each candidate electricalstimulation therapy of the plurality of different candidate electricalstimulation therapies to the initial eECAP signal, the one of theplurality of different candidate electrical stimulation therapies forsubsequent electrical stimulation, the processing circuitry isconfigured to select, based on the determination that the first eECAPsignal of the first candidate electrical stimulation therapy of theplurality of different candidate electrical stimulation therapiesmatches the initial eECAP signal, the first candidate electricalstimulation therapy for subsequent electrical stimulation.
 16. Thesystem of claim 15, wherein to determine that the first eECAP signal ofthe first candidate electrical stimulation therapy of the plurality ofdifferent candidate electrical stimulation therapies matches the initialeECAP signal, the processing circuitry is configured to determine that avalue of at least one parameter of the first eECAP signal is within arange based on a value of at least one parameter of the initial eECAPsignal.
 17. The system of claim 15, wherein to determine that the firsteECAP signal of the first candidate electrical stimulation therapy ofthe plurality of different candidate electrical stimulation therapiesmatches the initial eECAP signal, the processing circuitry is configuredto determine that a value of at least one parameter of the first eECAPsignal is less than a threshold value of at least one parameter of theinitial eECAP signal.
 18. The method of claim 15, wherein to compare therespective eECAP signal for each candidate electrical stimulationtherapy of the plurality of different candidate electrical stimulationtherapies to the initial eECAP signal, the processing circuitry isfurther configured to determine that a second eECAP signal of a secondcandidate electrical stimulation therapy of the plurality of differentcandidate electrical stimulation therapies is different from the initialeECAP signal.
 19. The method of claim 15, wherein to compare therespective eECAP signal for each candidate electrical stimulationtherapy of the plurality of different candidate electrical stimulationtherapies to the initial eECAP signal, the processing circuitry isfurther configured to compare at least one parameter of the respectiveeECAP signal for each candidate electrical stimulation therapy of theplurality of different candidate electrical stimulation therapies to atleast one parameter of the initial eECAP signal.
 20. A non-transitorycomputer-readable medium comprising instructions that, when executed,cause processing circuitry to: control a stimulation generator todeliver an initial electrical stimulation therapy defined by a set ofinitial therapy parameters to the patient; sense, in response to thedelivery of the initial electrical stimulation therapy, an initialelectrically evoked compound action potential (eECAP) signal; controlthe stimulation generator to deliver a plurality of different candidateelectrical stimulation therapies to the patient, each candidateelectrical stimulation therapy of the plurality of different candidateelectrical stimulation therapies defined by a respective set ofcandidate therapy parameters different from the set of initial therapyparameters; for each candidate electrical stimulation therapy of theplurality of different candidate electrical stimulation therapies,sense, in response to delivery of the candidate electrical stimulationtherapy, a respective eECAP signal; compare the respective eECAP signalfor each candidate electrical stimulation therapy of the plurality ofdifferent candidate electrical stimulation therapies to the initialeECAP signal; and select, based on the comparison of the respectiveeECAP signal for each candidate electrical stimulation therapy of theplurality of different candidate electrical stimulation therapies to theinitial eECAP signal, one of the plurality of different candidateelectrical stimulation therapies for subsequent electrical stimulation.